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Journal of Machine Learning Research (JMLR)

Proceedings of Machine Learning Research (PMLR)

Data-centric Machine Learning Research (DMLR)

Accepted papers

• Uncertainty in Graph Neural Networks: A Survey

  Fangxin Wang, Yuqing Liu, Kay Liu, Yibo Wang, Sourav Medya, Philip S. Yu, November 2024
  [openreview] [pdf] [bib]

• From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models

  Sean Welleck, Amanda Bertsch, Matthew Finlayson, Hailey Schoelkopf, Alex Xie, Graham Neubig, Ilia Kulikov, Zaid Harchaoui, November 2024
  [openreview] [pdf] [bib]
  Certifications: Survey

• Repositioning the Subject within Image

  Yikai Wang, Chenjie Cao, Ke Fan, Qiaole Dong, Yifan Li, Xiangyang Xue, Yanwei Fu, November 2024
  [openreview] [pdf] [bib] [code]

• FLR: Label-Mixture Regularization for Federated Learning with Noisy Labels

  Taehyeon Kim, Donggyu Kim, Se-Young Yun, November 2024
  [openreview] [pdf] [bib]

• Pretraining a Neural Operator in Lower Dimensions

  AmirPouya Hemmasian, Amir Barati Farimani, November 2024
  [openreview] [pdf] [bib] [code]

• Perception Stitching: Zero-Shot Perception Encoder Transfer for Visuomotor Robot Policies

  Pingcheng Jian, Easop Lee, Zachary I. Bell, Michael M. Zavlanos, Boyuan Chen, November 2024
  [openreview] [pdf] [bib] [code]

• Scale Equalization for Multi-Level Feature Fusion

  Bum Jun Kim, Sang Woo Kim, November 2024
  [openreview] [pdf] [bib] [code]

• Multi-LoRA Composition for Image Generation

  Ming Zhong, yelong shen, Shuohang Wang, Yadong Lu, Yizhu Jiao, Siru Ouyang, Donghan Yu, Jiawei Han, Weizhu Chen, November 2024
  [openreview] [pdf] [bib] [code]

• Trusted Aggregation (TAG): Backdoor Defense in Federated Learning

  Joseph Lavond, Minhao Cheng, Yao Li, November 2024
  [openreview] [pdf] [bib] [code]

• Zero-Order One-Point Gradient Estimate in Consensus-Based Distributed Stochastic Optimization

  Elissa Mhanna, Mohamad Assaad, November 2024
  [openreview] [pdf] [bib]

• Towards Empirical Interpretation of Internal Circuits and Properties in Grokked Transformers on Modular Polynomials

  Hiroki Furuta, Gouki Minegishi, Yusuke Iwasawa, Yutaka Matsuo, November 2024
  [openreview] [pdf] [bib] [code]

• Demonstration-Guided Multi-Objective Reinforcement Learning

  Junlin Lu, Patrick Mannion, Karl Mason, November 2024
  [openreview] [pdf] [bib] [code]

• Weighted L1 and L0 Regularization Using Proximal Operator Splitting Methods

  Zewude A. Berkessa, Patrik Waldmann, November 2024
  [openreview] [pdf] [bib]

• Reproducibility Study of "Languange-Image COnsistency"

  Konrad Szewczyk, Patrik Bartak, Mikhail Vlasenko, Fanmin Shi, November 2024
  [openreview] [pdf] [bib] [code]

• AnyV2V: A Tuning-Free Framework For Any Video-to-Video Editing Tasks

  Max Ku, Cong Wei, Weiming Ren, Huan Yang, Wenhu Chen, November 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility

• Mitigating Relative Over-Generalization in Multi-Agent Reinforcement Learning

  Ting Zhu, Yue Jin, Jeremie Houssineau, Giovanni Montana, November 2024
  [openreview] [pdf] [bib]

• An Investigation of Offline Reinforcement Learning in Factorisable Action Spaces

  Alex Beeson, David Ireland, Giovanni Montana, November 2024
  [openreview] [pdf] [bib] [code]

• Gaussian-Smoothed Sliced Probability Divergences

  Mokhtar Z. Alaya, Alain Rakotomamonjy, Maxime Berar, Gilles Gasso, November 2024
  [openreview] [pdf] [bib]

• Differentially Private Latent Diffusion Models

  Michael F Liu, Saiyue Lyu, Margarita Vinaroz, Mijung Park, November 2024
  [openreview] [pdf] [bib]

• On Intriguing Layer-Wise Properties of Robust Overfitting in Adversarial Training

  Duke Nguyen, Chaojian Yu, Vinoth Nandakumar, Young Choon Lee, Tongliang Liu, November 2024
  [openreview] [pdf] [bib] [code]

• Is Value Functions Estimation with Classification Plug-and- play for Offline Reinforcement Learning?

  Denis Tarasov, Kirill Brilliantov, Dmitrii Kharlapenko, November 2024
  [openreview] [pdf] [bib] [code]

• Improved Variational Bayesian Phylogenetic Inference using Mixtures

  Ricky Molén, Oskar Kviman, Jens Lagergren, November 2024
  [openreview] [pdf] [bib] [code]

• Video Diffusion Models: A Survey

  Andrew Melnik, Michal Ljubljanac, Cong Lu, Qi Yan, Weiming Ren, Helge Ritter, November 2024
  [openreview] [pdf] [bib]

• Mantis: Interleaved Multi-Image Instruction Tuning

  Dongfu Jiang, Xuan He, Huaye Zeng, Cong Wei, Max Ku, Qian Liu, Wenhu Chen, November 2024
  [openreview] [pdf] [bib] [code]

• Beyond Loss Functions: Exploring Data-Centric Approaches with Diffusion Model for Domain Generalization

  Sobhan Hemati, Mahdi Beitollahi, Amir Hossein Estiri, Bassel Al Omari, Soufiane Lamghari, Yasser H. Khalil, Xi Chen, Guojun Zhang, November 2024
  [openreview] [pdf] [bib]

• DrGNN: Deep Residual Graph Neural Network with Contrastive Learning

  Lecheng Zheng, Dongqi Fu, Ross Maciejewski, Jingrui He, November 2024
  [openreview] [pdf] [bib] [code]

• A Single Transformer for Scalable Vision-Language Modeling

  Yangyi Chen, Xingyao Wang, Hao Peng, Heng Ji, November 2024
  [openreview] [pdf] [bib] [code]

• Confidence-aware Denoised Fine-tuning of Off-the-shelf Models for Certified Robustness

  Suhyeok Jang, Seojin Kim, Jinwoo Shin, Jongheon Jeong, November 2024
  [openreview] [pdf] [bib] [code]

• Towards Backwards-Compatible Data with Confounded Domain Adaptation

  Calvin McCarter, November 2024
  [openreview] [pdf] [bib] [code]

• Feature learning as alignment: a structural property of gradient descent in non-linear neural networks

  Daniel Beaglehole, Ioannis Mitliagkas, Atish Agarwala, November 2024
  [openreview] [pdf] [bib]

• Bayesian Computation Meets Topology

  Julius von Rohrscheidt, Bastian Rieck, Sebastian M Schmon, November 2024
  [openreview] [pdf] [bib] [code]

• Chronos: Learning the Language of Time Series

  Abdul Fatir Ansari, Lorenzo Stella, Ali Caner Turkmen, Xiyuan Zhang, Pedro Mercado, Huibin Shen, Oleksandr Shchur, Syama Sundar Rangapuram, Sebastian Pineda Arango, Shubham Kapoor, Jasper Zschiegner, Danielle C. Maddix, Hao Wang, Michael W. Mahoney, Kari Torkkola, Andrew Gordon Wilson, Michael Bohlke-Schneider, Bernie Wang, November 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Language Models Speed Up Local Search for Finding Programmatic Policies

  Quazi Asif Sadmine, Hendrik Baier, Levi Lelis, November 2024
  [openreview] [pdf] [bib]

• CFASL: Composite Factor-Aligned Symmetry Learning for Disentanglement in Variational AutoEncoder

  Hee-Jun Jung, Jaehyoung Jeong, Kangil Kim, November 2024
  [openreview] [pdf] [bib] [code]

• Modular Federated Contrastive Learning with Twin Normalization for Resource-limited Clients

  Azadeh Motamedi, IL MIN KIM, November 2024
  [openreview] [pdf] [bib]

• Graphon-Explainer: Generating Model-Level Explanations for Graph Neural Networks using Graphons

  Sayan Saha, Sanghamitra Bandyopadhyay, November 2024
  [openreview] [pdf] [bib] [code]

• A Survey on Large Language Models for Critical Societal Domains: Finance, Healthcare, and Law

  Zhiyu Chen, Jing Ma, Xinlu Zhang, Nan Hao, An Yan, Armineh Nourbakhsh, Xianjun Yang, Julian McAuley, Linda Ruth Petzold, William Yang Wang, November 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Survey

• Simple Steps to Success: A Method for Step-Based Counterfactual Explanations

  Jenny Hamer, Nicholas Perello, Jason Valladares, Vignesh Viswanathan, Yair Zick, November 2024
  [openreview] [pdf] [bib]

• Autoencoding Hyperbolic Representation for Adversarial Generation

  Eric Qu, Dongmian Zou, November 2024
  [openreview] [pdf] [bib] [code]

• Feature Alignment: Rethinking Efficient Active Learning via Proxy in the Context of Pre-trained Models

  Ziting Wen, Oscar Pizarro, Stefan B. Williams, November 2024
  [openreview] [pdf] [bib] [code]

• Bandits with Mean Bounds

  Nihal Sharma, Soumya Basu, Karthikeyan Shanmugam, Sanjay Shakkottai, November 2024
  [openreview] [pdf] [bib]

• Merging Text Transformer Models from Different Initializations

  Neha Verma, Maha Elbayad, November 2024
  [openreview] [pdf] [bib] [code]

• Deep-Graph-Sprints: Accelerated Representation Learning in Continuous-Time Dynamic Graphs

  Ahmad Naser Eddin, Jacopo Bono, David Oliveira Aparicio, Hugo Ferreira, Pedro Manuel Pinto Ribeiro, Pedro Bizarro, November 2024
  [openreview] [pdf] [bib]

• Contrastive Learning with Adaptive Neighborhoods for Brain Age Prediction on 3D Stiffness Maps

  Jakob Träuble, Lucy V Hiscox, Curtis Johnson, Carola-Bibiane Schönlieb, Gabriele S Kaminski Schierle, Angelica I Aviles-Rivero, November 2024
  [openreview] [pdf] [bib] [code]

• Heterogeneous graph adaptive flow network

  Lu Yiqi, Feng Ji, Wee Peng Tay, November 2024
  [openreview] [pdf] [bib] [code]

• MoCaE: Mixture of Calibrated Experts Significantly Improves Object Detection

  Kemal Oksuz, Selim Kuzucu, Tom Joy, Puneet K. Dokania, November 2024
  [openreview] [pdf] [bib] [code]

• IM-Context: In-Context Learning for Imbalanced Regression Tasks

  Ismail Nejjar, Faez Ahmed, Olga Fink, November 2024
  [openreview] [pdf] [bib]

• Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

  Zeyu Han, Chao Gao, Jinyang Liu, Jeff Zhang, Sai Qian Zhang, November 2024
  [openreview] [pdf] [bib]

• Federated Graph Learning with Graphless Clients

  Xingbo Fu, Song Wang, Yushun Dong, Binchi Zhang, Chen Chen, Jundong Li, November 2024
  [openreview] [pdf] [bib]

• One by One, Continual Coordinating with Humans via Hyper-Teammate Identification

  Cong Guan, Feng Chen, Ke Xue, Chunpeng Fan, Lichao Zhang, Ziqian Zhang, Pengyao Zhao, Zongzhang Zhang, Chao Qian, Lei Yuan, Yang Yu, November 2024
  [openreview] [pdf] [bib] [code]

• PLUM: Improving Inference Efficiency By Leveraging Repetition-Sparsity Trade-Off

  Sachit Kuhar, Yash Jain, Alexey Tumanov, November 2024
  [openreview] [pdf] [bib] [code]

• Global Convergence Guarantees for Federated Policy Gradient Methods with Adversaries

  Swetha Ganesh, Jiayu Chen, Gugan Thoppe, Vaneet Aggarwal, November 2024
  [openreview] [pdf] [bib]

• The Klarna Product Page Dataset: Web Element Nomination with Graph Neural Networks and Large Language Models

  Alexandra Hotti, Riccardo Sven Risuleo, Stefan Magureanu, Aref Moradi, Jens Lagergren, November 2024
  [openreview] [pdf] [bib] [code]

• Towards Provable Log Density Policy Gradient

  Pulkit Katdare, Anant A Joshi, Katherine Rose Driggs-Campbell, November 2024
  [openreview] [pdf] [bib]

• Practical Synthesis of Mixed-Tailed Data with Normalizing Flows

  Saba Amiri, Eric Nalisnick, Adam Belloum, Sander Klous, Leon Gommans, November 2024
  [openreview] [pdf] [bib]

• Single-Shot Plug-and-Play Methods for Inverse Problems

  Yanqi Cheng, Lipei Zhang, Zhenda Shen, Shujun Wang, Lequan Yu, Raymond H. Chan, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero, November 2024
  [openreview] [pdf] [bib]

• Hashing with Uncertainty Quantification via Sampling-based Hypothesis Testing

  Yucheng Wang, Mingyuan Zhou, Xiaoning Qian, November 2024
  [openreview] [pdf] [bib] [code]

• Adaptively Robust and Sparse $K$-means Clustering

  HAO LI, Shonosuke Sugasawa, Shota Katayama, November 2024
  [openreview] [pdf] [bib] [code]

• Modular Quantization-Aware Training for 6D Object Pose Estimation

  Saqib Javed, Chengkun Li, Andrew Lawrence Price, Yinlin Hu, Mathieu Salzmann, November 2024
  [openreview] [pdf] [bib] [code]

• SASSL: Enhancing Self-Supervised Learning via Neural Style Transfer

  Renan A. Rojas-Gomez, Karan Singhal, Ali Etemad, Alex Bijamov, Warren Richard Morningstar, Philip Andrew Mansfield, November 2024
  [openreview] [pdf] [bib]

• Analyzing the Impact of Learnable Softmax Temperature in Contrastive Visual-Textual Alignment Systems: Benefits, Drawbacks, and Alternative Approaches

  Zhun Sun, Chao Li, November 2024
  [openreview] [pdf] [bib] [code]

• Sparsifying Bayesian neural networks with latent binary variables and normalizing flows

  Lars Skaaret-Lund, Geir Storvik, Aliaksandr Hubin, November 2024
  [openreview] [pdf] [bib] [code]

• Interpreting CLIP: Insights on the Robustness to ImageNet Distribution Shifts

  Jonathan Crabbé, Pau Rodriguez, Vaishaal Shankar, Luca Zappella, Arno Blaas, November 2024
  [openreview] [pdf] [bib]

• Class-Discriminative Attention Maps for Vision Transformers

  Lennart Brocki, Jakub Binda, Neo Christopher Chung, November 2024
  [openreview] [pdf] [bib] [code]

• Beyond Text: Utilizing Vocal Cues to Improve Decision Making in LLMs for Robot Navigation Tasks

  Xingpeng Sun, Haoming Meng, Souradip Chakraborty, Amrit Bedi, Aniket Bera, November 2024
  [openreview] [pdf] [bib]

• Efficient Model-Agnostic Multi-Group Equivariant Networks

  Razan Baltaji, Sourya Basu, Lav R. Varshney, November 2024
  [openreview] [pdf] [bib] [code]

• Incorporating Inductive Biases to Energy-based Generative Models

  Yukun Li, Liping Liu, November 2024
  [openreview] [pdf] [bib]

• SelfXit: An Unsupervised Early Exit Mechanism for Deep Neural Networks

  Hossein KhademSohi, Mohammadamin Abedi, Yani Ioannou, STEVE DREW, Pooyan Jamshidi, Hadi Hemmati, October 2024
  [openreview] [pdf] [bib] [code]

• PerSEval: Assessing Personalization in Text Summarizers

  Sourish Dasgupta, Ankush Chander, Tanmoy Chakraborty, Parth Borad, Isha Motiyani, October 2024
  [openreview] [pdf] [bib] [code]

• Risk-Controlling Model Selection via Guided Bayesian Optimization

  Bracha Laufer-Goldshtein, Adam Fisch, Regina Barzilay, Tommi Jaakkola, October 2024
  [openreview] [pdf] [bib] [code]

• Learning Unlabeled Clients Divergence for Federated Semi-Supervised Learning via Anchor Model Aggregation

  Marawan Elbatel, Hualiang Wang, Jixiang CHEN, Hao Wang, Xiaomeng Li, October 2024
  [openreview] [pdf] [bib] [code]

• Dependency Structure Search Bayesian Optimization for Decision Making Models

  Mohit Rajpal, Lac Gia Tran, Yehong Zhang, Bryan Kian Hsiang Low, October 2024
  [openreview] [pdf] [bib]

• Let There be Direction in Hypergraph Neural Networks

  Stefano Fiorini, Stefano Coniglio, Michele Ciavotta, Alessio Del Bue, October 2024
  [openreview] [pdf] [bib]

• How Far Are We From AGI: Are LLMs All We Need?

  Tao Feng, Chuanyang Jin, Jingyu Liu, Kunlun Zhu, Haoqin Tu, Zirui Cheng, Guanyu Lin, Jiaxuan You, October 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Survey

• Deep Kernel Learning of Nonlinear Latent Force Models

  Jacob Moss, Jeremy England, Pietro Lio, October 2024
  [openreview] [pdf] [bib]

• Multi-Accurate CATE is Robust to Unknown Covariate Shifts

  Christoph Kern, Michael P. Kim, Angela Zhou, October 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• Locally Adaptive Federated Learning

  Sohom Mukherjee, Nicolas Loizou, Sebastian U Stich, October 2024
  [openreview] [pdf] [bib]

• Learning under Imitative Strategic Behavior with Unforeseeable Outcomes

  Tian Xie, Zhiqun Zuo, Mohammad Mahdi Khalili, Xueru Zhang, October 2024
  [openreview] [pdf] [bib] [code]

• KD-BIRL: Kernel Density Bayesian Inverse Reinforcement Learning

  Aishwarya Mandyam, Didong Li, Andrew Jones, Diana Cai, Barbara E Engelhardt, October 2024
  [openreview] [pdf] [bib]

• Offline Deep Reinforcement Learning for Visual Distractions via Domain Adversarial Training

  Jen-Yen Chang, Thomas Westfechtel, Takayuki Osa, Tatsuya Harada, October 2024
  [openreview] [pdf] [bib] [code]

• Self-supervised Color Generalization in Reinforcement Learning

  Matthias Weissenbacher, Evangelos Routis, Yoshinobu Kawahara, October 2024
  [openreview] [pdf] [bib] [code]

• Approximations to the Fisher Information Metric of Deep Generative Models for Out-Of-Distribution Detection

  Sam Dauncey, Christopher C. Holmes, Christopher Williams, Fabian Falck, October 2024
  [openreview] [pdf] [bib] [code]

• Undetectable Steganography for Language Models

  Or Zamir, October 2024
  [openreview] [pdf] [bib] [code]

• Equivariant Symmetry Breaking Sets

  YuQing Xie, Tess Smidt, October 2024
  [openreview] [pdf] [bib] [code]

• GraphMaker: Can Diffusion Models Generate Large Attributed Graphs?

  Mufei Li, Eleonora Kreacic, Vamsi K. Potluru, Pan Li, October 2024
  [openreview] [pdf] [bib] [code]

• AGG: Amortized Generative 3D Gaussians for Single Image to 3D

  Dejia Xu, Ye Yuan, Morteza Mardani, Sifei Liu, Jiaming Song, Zhangyang Wang, Arash Vahdat, October 2024
  [openreview] [pdf] [bib]

• More Agents Is All You Need

  junyou li, Qin Zhang, Yangbin Yu, QIANG FU, Deheng Ye, October 2024
  [openreview] [pdf] [bib] [code]

• Certified Robustness against Sparse Adversarial Perturbations via Data Localization

  Ambar Pal, Rene Vidal, Jeremias Sulam, October 2024
  [openreview] [pdf] [bib] [code]

• Faster optimal univariate microaggregation

  Felix I. Stamm, Michael T Schaub, October 2024
  [openreview] [pdf] [bib] [code]

• VideoGLUE: Video General Understanding Evaluation of Foundation Models

  Liangzhe Yuan, Nitesh Bharadwaj Gundavarapu, Long Zhao, Hao Zhou, Yin Cui, Lu Jiang, Xuan Yang, Menglin Jia, Tobias Weyand, Luke Friedman, Mikhail Sirotenko, Huisheng Wang, Florian Schroff, Hartwig Adam, Ming-Hsuan Yang, Ting Liu, Boqing Gong, October 2024
  [openreview] [pdf] [bib] [code]

• Mixture of Latent Experts Using Tensor Products

  Zhan Su, Fengran Mo, Prayag Tiwari, Benyou Wang, Qiuchi Li, Jian-Yun Nie, Jakob Grue Simonsen, October 2024
  [openreview] [pdf] [bib] [code]

• Greedy Growing Enables High-Resolution Pixel-Based Diffusion Models

  Cristina Nader Vasconcelos, Abdullah Rashwan, Austin Waters, Trevor Walker, Keyang Xu, Jimmy Yan, Rui Qian, Yeqing Li, SHIXIN LUO, Yasumasa Onoe, Zarana Parekh, Ivana Kajic, Mandy Guo, Wenlei Zhou, Sarah Rosston, Roopal Garg, Hongliang Fei, Jordi Pont-Tuset, Su Wang, Henna Nandwani, Andrew Bunner, Kevin Swersky, David J. Fleet, Oliver Wang, Jason Michael Baldridge, October 2024
  [openreview] [pdf] [bib]

• Selective Classification Under Distribution Shifts

  Hengyue Liang, Le Peng, Ju Sun, October 2024
  [openreview] [pdf] [bib] [code]

• A Distance-based Anomaly Detection Framework for Deep Reinforcement Learning

  Hongming Zhang, Ke Sun, bo xu, Linglong Kong, Martin Müller, October 2024
  [openreview] [pdf] [bib]

• Persona-aware Generative Model for Code-mixed Language

  Ayan Sengupta, Md Shad Akhtar, Tanmoy Chakraborty, October 2024
  [openreview] [pdf] [bib] [code]

• From Complexity to Clarity: Analytical Expressions of Deep Neural Network Weights via Clifford Algebra and Convexity

  Mert Pilanci, October 2024
  [openreview] [pdf] [bib]

• Controlling the Fidelity and Diversity of Deep Generative Models via Pseudo Density

  Shuangqi Li, Chen Liu, Tong Zhang, Hieu Le, Sabine Susstrunk, Mathieu Salzmann, October 2024
  [openreview] [pdf] [bib]

• The Trifecta: Three simple techniques for training deeper Forward-Forward networks

  Thomas Dooms, Ing Jyh Tsang, Jose Oramas, October 2024
  [openreview] [pdf] [bib] [code]

• Neural Likelihood Approximation for Integer Valued Time Series Data

  Luke O'Loughlin, Andrew J. Black, John Maclean, October 2024
  [openreview] [pdf] [bib] [code]

• Graph Knowledge Distillation to Mixture of Experts

  Pavel Rumiantsev, Mark Coates, October 2024
  [openreview] [pdf] [bib]
  Certifications: Written by Expert Reviewer

• MoMA: Model-based Mirror Ascent for Offline Reinforcement Learning

  Mao Hong, Zhiyue Zhang, Yue Wu, Yanxun Xu, October 2024
  [openreview] [pdf] [bib] [code]

• Credal Bayesian Deep Learning

  Michele Caprio, Souradeep Dutta, Kuk Jin Jang, Vivian Lin, Radoslav Ivanov, Oleg Sokolsky, Insup Lee, October 2024
  [openreview] [pdf] [bib] [code]

• Generating Less Certain Adversarial Examples Improves Robust Generalization

  Minxing Zhang, Michael Backes, Xiao Zhang, October 2024
  [openreview] [pdf] [bib] [code]

• Analyzing Deep Transformer Models for Time Series Forecasting via Manifold Learning

  Ilya Kaufman, Omri Azencot, October 2024
  [openreview] [pdf] [bib] [code]

• Corrective Machine Unlearning

  Shashwat Goel, Ameya Prabhu, Philip Torr, Ponnurangam Kumaraguru, Amartya Sanyal, October 2024
  [openreview] [pdf] [bib] [code]

• Neural incomplete factorization: learning preconditioners for the conjugate gradient method

  Paul Häusner, Ozan Öktem, Jens Sjölund, October 2024
  [openreview] [pdf] [bib] [code]

• Tree Ensembles for Contextual Bandits

  Hannes Nilsson, Rikard Johansson, Niklas Åkerblom, Morteza Haghir Chehreghani, October 2024
  [openreview] [pdf] [bib]

• Can We Count on LLMs? The Fixed-Effect Fallacy and Claims of GPT-4 Capabilities

  Thomas Ball, Shuo Chen, Cormac Herley, October 2024
  [openreview] [pdf] [bib]

• Nonlinear Behaviour of Critical Points for a Simple Neural Network

  Gerrit Welper, October 2024
  [openreview] [pdf] [bib]

• Measuring Orthogonality in Representations of Generative Models

  Robin C. Geyer, Alessandro Torcinovich, João B. S. Carvalho, Alexander Meyer, Joachim M. Buhmann, October 2024
  [openreview] [pdf] [bib] [code]

• Mislabeled examples detection viewed as probing machine learning models: concepts, survey and extensive benchmark

  Thomas George, Pierre Nodet, Alexis Bondu, Vincent Lemaire, October 2024
  [openreview] [pdf] [bib] [code]

• Coordinate Transform Fourier Neural Operators for Symmetries in Physical Modelings

  Wenhan Gao, Ruichen Xu, Hong Wang, Yi Liu, October 2024
  [openreview] [pdf] [bib] [code]

• Reproducibility and Geometric Intrinsic Dimensionality: An Investigation on Graph Neural Network Research.

  Tobias Hille, Maximilian Stubbemann, Tom Hanika, October 2024
  [openreview] [pdf] [bib]
  Certifications: Reproducibility

• Continual Learning in Open-vocabulary Classification with Complementary Memory Systems

  Zhen Zhu, Weijie Lyu, Yao Xiao, Derek Hoiem, October 2024
  [openreview] [pdf] [bib] [code]

• AGaLiTe: Approximate Gated Linear Transformers for Online Reinforcement Learning

  Subhojeet Pramanik, Esraa Elelimy, Marlos C. Machado, Adam White, October 2024
  [openreview] [pdf] [bib] [code]

• ECG Semantic Integrator (ESI): A Foundation ECG Model Pretrained with LLM-Enhanced Cardiological Text

  Han Yu, Peikun Guo, Akane Sano, October 2024
  [openreview] [pdf] [bib]

• LeOCLR: Leveraging Original Images for Contrastive Learning of Visual Representations

  Mohammad Alkhalefi, Georgios Leontidis, Mingjun Zhong, October 2024
  [openreview] [pdf] [bib]

• Learning Sub-Second Routing Optimization in Computer Networks requires Packet-Level Dynamics

  Andreas Boltres, Niklas Freymuth, Patrick Jahnke, Holger Karl, Gerhard Neumann, October 2024
  [openreview] [pdf] [bib]

• Structure-Preserving Network Compression Via Low-Rank Induced Training Through Linear Layers Composition

  Ismail Alkhouri, Xitong Zhang, Rongrong Wang, October 2024
  [openreview] [pdf] [bib] [code]

• ProFeAT: Projected Feature Adversarial Training for Self-Supervised Learning of Robust Representations

  Sravanti Addepalli, Priyam Dey, Venkatesh Babu Radhakrishnan, October 2024
  [openreview] [pdf] [bib] [code]

• Recurrent Inertial Graph-Based Estimator (RING): A Single Pluripotent Inertial Motion Tracking Solution

  Simon Bachhuber, Ive Weygers, Dustin Lehmann, Mischa Dombrowski, Thomas Seel, October 2024
  [openreview] [pdf] [bib] [code]

• Learning-Based Link Anomaly Detection in Continuous-Time Dynamic Graphs

  Tim Postuvan, Claas Grohnfeldt, Michele Russo, Giulio Lovisotto, October 2024
  [openreview] [pdf] [bib] [code]

• Why Fine-grained Labels in Pretraining Benefit Generalization?

  Guan Zhe Hong, Yin Cui, Ariel Fuxman, Stanley H. Chan, Enming Luo, October 2024
  [openreview] [pdf] [bib]

• Quantization Variation: A New Perspective on Training Transformers with Low-Bit Precision

  Xijie Huang, Zhiqiang Shen, Pingcheng Dong, Kwang-Ting Cheng, October 2024
  [openreview] [pdf] [bib] [code]

• Stochastic Bandits for Egalitarian Assignment

  Eugene Lim, Vincent Y. F. Tan, Harold Soh, October 2024
  [openreview] [pdf] [bib]

• In-context Learning with Retrieved Demonstrations for Language Models: A Survey

  Man Luo, Xin Xu, Yue Liu, Panupong Pasupat, Mehran Kazemi, October 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Survey

• IRWE: Inductive Random Walk for Joint Inference of Identity and Position Network Embedding

  Meng QIN, Dit-Yan Yeung, October 2024
  [openreview] [pdf] [bib]

• Adaptive Training Distributions with Scalable Online Bilevel Optimization

  David Grangier, Pierre Ablin, Awni Hannun, October 2024
  [openreview] [pdf] [bib]

• Support-Set Context Matters for Bongard Problems

  Nikhil Raghuraman, Adam W Harley, Leonidas Guibas, October 2024
  [openreview] [pdf] [bib] [code]

• A Probabilistic Model behind Self- Supervised Learning

  Alice Bizeul, Bernhard Schölkopf, Carl Allen, October 2024
  [openreview] [pdf] [bib] [code]

• From Persona to Personalization: A Survey on Role-Playing Language Agents

  Jiangjie Chen, Xintao Wang, Rui Xu, Siyu Yuan, Yikai Zhang, Wei Shi, Jian Xie, Shuang Li, Ruihan Yang, Tinghui Zhu, Aili Chen, Nianqi Li, Lida Chen, Caiyu Hu, Siye Wu, Scott Ren, Ziquan Fu, Yanghua Xiao, October 2024
  [openreview] [pdf] [bib]
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• LINOCS: Lookahead Inference of Networked Operators for Continuous Stability

  Noga Mudrik, Eva Yezerets, Yenho Chen, Christopher John Rozell, Adam Shabti Charles, October 2024
  [openreview] [pdf] [bib] [code]

• Robust Stochastic Optimization via Gradient Quantile Clipping

  Ibrahim Merad, Stéphane Gaïffas, October 2024
  [openreview] [pdf] [bib]

• Implicit Neural Representations for Robust Joint Sparse-View CT Reconstruction

  Jiayang Shi, Junyi Zhu, Daniel Pelt, Joost Batenburg, Matthew B. Blaschko, October 2024
  [openreview] [pdf] [bib] [code]

• Score-based Explainability for Graph Representations

  Ehsan Hajiramezanali, Sepideh Maleki, Max W Shen, Kangway V. Chuang, Tommaso Biancalani, Gabriele Scalia, October 2024
  [openreview] [pdf] [bib]

• Scaling Up Bayesian Neural Networks with Neural Networks

  Zahra Moslemi, Yang Meng, Shiwei Lan, Babak Shahbaba, October 2024
  [openreview] [pdf] [bib] [code]

• PriViT: Vision Transformers for Private Inference

  Naren Dhyani, Jianqiao Cambridge Mo, Patrick Yubeaton, Minsu Cho, Ameya Joshi, Siddharth Garg, Brandon Reagen, Chinmay Hegde, October 2024
  [openreview] [pdf] [bib] [code]

• Reward Guided Latent Consistency Distillation

  Jiachen Li, Weixi Feng, Wenhu Chen, William Yang Wang, October 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• Revisiting Deep Feature Reconstruction for Logical and Structural Industrial Anomaly Detection

  Sukanya Patra, Souhaib Ben Taieb, October 2024
  [openreview] [pdf] [bib] [code]

• Meta-Learning under Task Shift

  Lei Sun, Yusuke Tanaka, Tomoharu Iwata, October 2024
  [openreview] [pdf] [bib]

• Data Valuation in the Absence of a Reliable Validation Set

  Himanshu Jahagirdar, Jiachen T. Wang, Ruoxi Jia, October 2024
  [openreview] [pdf] [bib]
  Certifications: Featured

• LInK: Learning Joint Representations of Design and Performance Spaces through Contrastive Learning for Mechanism Synthesis

  Amin Heyrani Nobari, Akash Srivastava, Dan Gutfreund, Kai Xu, Faez Ahmed, October 2024
  [openreview] [pdf] [bib] [code]

• Universal Functional Regression with Neural Operator Flows

  Yaozhong Shi, Angela F Gao, Zachary E Ross, Kamyar Azizzadenesheli, October 2024
  [openreview] [pdf] [bib] [code]

• A Theoretical Framework for Zeroth-Order Budget Convex Optimization

  François Bachoc, Tommaso Cesari, Roberto Colomboni, Andrea Paudice, October 2024
  [openreview] [pdf] [bib]

• Plug, Play, and Generalize: Length Extrapolation with Pointer-Augmented Neural Memory

  Hung Le, Dung Nguyen, Kien Do, Svetha Venkatesh, Truyen Tran, October 2024
  [openreview] [pdf] [bib] [code]

• A Unified Hallucination Mitigation Framework for Large Vision-Language Models

  Yue Chang, Liqiang Jing, Xiaopeng Zhang, Yue Zhang, October 2024
  [openreview] [pdf] [bib] [code]

• Simultaneous Dimensionality Reduction: A Data Efficient Approach for Multimodal Representations Learning

  Eslam Abdelaleem, Ahmed Roman, K. Michael Martini, Ilya Nemenman, October 2024
  [openreview] [pdf] [bib]

• Reducing Variance in Meta-Learning via Laplace Approximation for Regression Tasks

  Alfredo Reichlin, Gustaf Tegnér, Miguel Vasco, Hang Yin, Mårten Björkman, Danica Kragic, October 2024
  [openreview] [pdf] [bib] [code]

• Budget-Aware Sequential Brick Assembly with Efficient Constraint Satisfaction

  Seokjun Ahn, Jungtaek Kim, Minsu Cho, Jaesik Park, October 2024
  [openreview] [pdf] [bib] [code]

• Finding Adversarially Robust Graph Lottery Tickets

  Subhajit Dutta Chowdhury, Zhiyu Ni, Qingyuan Peng, Souvik Kundu, Pierluigi Nuzzo, October 2024
  [openreview] [pdf] [bib]

• Attention Normalization Impacts Cardinality Generalization in Slot Attention

  Markus Krimmel, Jan Achterhold, Joerg Stueckler, October 2024
  [openreview] [pdf] [bib] [code]

• Gromov-Wasserstein-like Distances in the Gaussian Mixture Models Space

  Antoine Salmona, Agnes Desolneux, Julie Delon, October 2024
  [openreview] [pdf] [bib] [code]

• UCB Exploration for Fixed-Budget Bayesian Best Arm Identification

  Rong J.B. Zhu, Yanqi Qiu, October 2024
  [openreview] [pdf] [bib] [code]

• Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization

  Ramnath Kumar, Kushal Alpesh Majmundar, Dheeraj Mysore Nagaraj, Arun Suggala, October 2024
  [openreview] [pdf] [bib]

• Towards Trustworthy Reranking: A Simple yet Effective Abstention Mechanism

  Hippolyte Gisserot-Boukhlef, Manuel Faysse, Emmanuel Malherbe, CELINE HUDELOT, Pierre Colombo, October 2024
  [openreview] [pdf] [bib]

• GraphPrivatizer: Improved Structural Differential Privacy for Graph Neural Networks

  Rucha Bhalchandra Joshi, Patrick Indri, Subhankar Mishra, October 2024
  [openreview] [pdf] [bib] [code]

• Do not trust what you trust: Miscalibration in Semisupervised Learning

  Shambhavi Mishra, Balamurali Murugesan, Ismail Ben Ayed, Marco Pedersoli, Jose Dolz, September 2024
  [openreview] [pdf] [bib] [code]

• Diffusion Models with Deterministic Normalizing Flow Priors

  Mohsen Zand, Ali Etemad, Michael Greenspan, September 2024
  [openreview] [pdf] [bib] [code]

• Equivariant Graph Learning for High-density Crowd Trajectories Modeling

  Yang Liu, Zinan Zheng, Yu Rong, Jia Li, September 2024
  [openreview] [pdf] [bib] [code]

• Efficient Identification of Direct Causal Parents via Invariance and Minimum Error Testing

  Minh Nguyen, Mert R. Sabuncu, September 2024
  [openreview] [pdf] [bib] [code]

• Strategies for Pretraining Neural Operators

  Anthony Zhou, Cooper Lorsung, AmirPouya Hemmasian, Amir Barati Farimani, September 2024
  [openreview] [pdf] [bib] [code]

• Linear Weight Interpolation Leads to Transient Performance Gains

  Gaurav Iyer, Gintare Karolina Dziugaite, David Rolnick, September 2024
  [openreview] [pdf] [bib]

• A Semi-Bayesian Nonparametric Estimator of the Maximum Mean Discrepancy Measure: Applications in Goodness-of-Fit Testing and Generative Adversarial Networks

  Forough Fazeli-Asl, Michael Minyi Zhang, Lizhen Lin, September 2024
  [openreview] [pdf] [bib]

• Learning Hierarchical Relational Representations through Relational Convolutions

  Awni Altabaa, John Lafferty, September 2024
  [openreview] [pdf] [bib] [code]

• The Impact of Syntactic and Semantic Proximity on Machine Translation with Back-Translation

  Nicolas Guerin, Emmanuel Chemla, Shane Steinert-Threlkeld, September 2024
  [openreview] [pdf] [bib]

• Improving Generalization of Complex Models under Unbounded Loss Using PAC-Bayes Bounds

  Xitong Zhang, Avrajit Ghosh, Guangliang Liu, Rongrong Wang, September 2024
  [openreview] [pdf] [bib]

• Contrastive Class Anchor Learning for Open Set Object Recognition in Driving Scenes

  Zizhao Li, Kourosh Khoshelham, Joseph West, September 2024
  [openreview] [pdf] [bib]

• Simple Drop-in LoRA Conditioning on Attention Layers Will Improve Your Diffusion Model

  Joo Young Choi, Jaesung R. Park, Inkyu Park, Jaewoong Cho, Albert No, Ernest K. Ryu, September 2024
  [openreview] [pdf] [bib] [code]

• On Safety in Safe Bayesian Optimization

  Christian Fiedler, Johanna Menn, Lukas Kreisköther, Sebastian Trimpe, September 2024
  [openreview] [pdf] [bib] [code]

• IMProv: Inpainting-based Multimodal Prompting for Computer Vision Tasks

  Jiarui Xu, Yossi Gandelsman, Amir Bar, Jianwei Yang, Jianfeng Gao, Trevor Darrell, Xiaolong Wang, September 2024
  [openreview] [pdf] [bib]

• Adversarial Attacks on Online Learning to Rank with Stochastic Click Models

  Zichen Wang, Rishab Balasubramanian, Hui Yuan, chenyu song, Mengdi Wang, Huazheng Wang, September 2024
  [openreview] [pdf] [bib] [code]

• Tweedie Moment Projected Diffusions for Inverse Problems

  Benjamin Boys, Mark Girolami, Jakiw Pidstrigach, Sebastian Reich, Alan Mosca, Omer Deniz Akyildiz, September 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• Revisiting Energy Based Models as Policies: Ranking Noise Contrastive Estimation and Interpolating Energy Models

  Sumeet Singh, Stephen Tu, Vikas Sindhwani, September 2024
  [openreview] [pdf] [bib]

• Non-backtracking Graph Neural Networks

  Seonghyun Park, Narae Ryu, Gahee Kim, Dongyeop Woo, Se-Young Yun, Sungsoo Ahn, September 2024
  [openreview] [pdf] [bib] [code]

• Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connections

  Gabriel Loaiza-Ganem, Brendan Leigh Ross, Rasa Hosseinzadeh, Anthony L. Caterini, Jesse C. Cresswell, September 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Survey Written by Expert Reviewer

• Graph Cuts with Arbitrary Size Constraints Through Optimal Transport

  Chakib Fettal, lazhar labiod, Mohamed Nadif, September 2024
  [openreview] [pdf] [bib] [code]

• Reward Poisoning on Federated Reinforcement Learning

  Evelyn Ma, S. Rasoul Etesami, Praneet Rathi, September 2024
  [openreview] [pdf] [bib]

• Variational Inference on the Final-Layer Output of Neural Networks

  Yadi Wei, Roni Khardon, September 2024
  [openreview] [pdf] [bib] [code]

• Learning multi-modal generative models with permutation-invariant encoders and tighter variational objectives

  Marcel Hirt, Domenico Campolo, Victoria Leong, Juan-Pablo Ortega, September 2024
  [openreview] [pdf] [bib] [code]

• Noise Stability Optimization for Finding Flat Minima: A Hessian-based Regularization Approach

  Hongyang R. Zhang, Dongyue Li, Haotian Ju, September 2024
  [openreview] [pdf] [bib] [code]

• Conservative Evaluation of Offline Policy Learning

  Hager Radi Abdelwahed, Josiah P. Hanna, Matthew E. Taylor, September 2024
  [openreview] [pdf] [bib]

• Decomposition of Equivariant Maps via Invariant Maps: Application to Universal Approximation under Symmetry.

  Akiyoshi Sannai, Yuuki Takai, Matthieu Cordonnier, September 2024
  [openreview] [pdf] [bib]

• Threshold Moving for Online Class Imbalance Learning with Dynamic Evolutionary Cost Vector

  Peijia Qin, Shuxian Li, Xiaoqun Liu, Zubin Zheng, Siang Yew Chong, September 2024
  [openreview] [pdf] [bib] [code]

• Continual Adaptation of Vision Transformers for Federated Learning

  Shaunak Halbe, James Seale Smith, Junjiao Tian, Zsolt Kira, September 2024
  [openreview] [pdf] [bib] [code]

• On the Equivalence of Graph Convolution and Mixup

  Xiaotian Han, Hanqing Zeng, Yu Chen, Shaoliang Nie, Jingzhou Liu, Kanika Narang, Zahra Shakeri, Karthik Abinav Sankararaman, Song Jiang, Madian Khabsa, Qifan Wang, Xia Hu, September 2024
  [openreview] [pdf] [bib]

• M$^3$PL: Identifying and Exploiting View Bias of Prompt Learning

  Chujie Zhao, Tianren Zhang, Guanyu Chen, Yizhou Jiang, Feng Chen, September 2024
  [openreview] [pdf] [bib] [code]

• RLHF Workflow: From Reward Modeling to Online RLHF

  Hanze Dong, Wei Xiong, Bo Pang, Haoxiang Wang, Han Zhao, Yingbo Zhou, Nan Jiang, Doyen Sahoo, Caiming Xiong, Tong Zhang, September 2024
  [openreview] [pdf] [bib] [code]

• Calibrated Uncertainty Quantification for Operator Learning via Conformal Prediction

  Ziqi Ma, David Pitt, Kamyar Azizzadenesheli, Anima Anandkumar, September 2024
  [openreview] [pdf] [bib] [code]

• Learned feature representations are biased by complexity, learning order, position, and more

  Andrew Kyle Lampinen, Stephanie C.Y. Chan, Katherine Hermann, September 2024
  [openreview] [pdf] [bib] [code]

• Prioritized Federated Learning: Leveraging Non-Priority Clients for Targeted Model Improvement

  Aditya Narayan Ravi, Ilan Shomorony, September 2024
  [openreview] [pdf] [bib] [code]

• HiFE: Hierarchical Feature Ensemble Framework for Few-shot Hypotheses Adaptation

  Yongfeng Zhong, Haoang Chi, Feng Liu, Xiao-Ming Wu, Bo Han, September 2024
  [openreview] [pdf] [bib] [code]

• Attribute Graphs Underlying Molecular Generative Models: Path to Learning with Limited Data

  Samuel C Hoffman, Payel Das, Karthikeyan Shanmugam, Kahini Wadhawan, Prasanna Sattigeri, September 2024
  [openreview] [pdf] [bib]

• Identifiable Causal Inference with Noisy Treatment and No Side Information

  Antti Pöllänen, Pekka Marttinen, September 2024
  [openreview] [pdf] [bib] [code]

• Hierarchically branched diffusion models leverage dataset structure for class-conditional generation

  Alex M Tseng, Max W Shen, Tommaso Biancalani, Gabriele Scalia, September 2024
  [openreview] [pdf] [bib] [code]

• SA-MLP: Distilling Graph Knowledge from GNNs into Structure-Aware MLP

  Jie Chen, Mingyuan Bai, Shouzhen Chen, Junbin Gao, Junping Zhang, Jian Pu, September 2024
  [openreview] [pdf] [bib] [code]

• Generative Models are Self-Watermarked: Declaring Model Authentication through Re-Generation

  Aditya Desu, Xuanli He, Qiongkai Xu, Wei Lu, September 2024
  [openreview] [pdf] [bib]

• Incremental Spatial and Spectral Learning of Neural Operators for Solving Large-Scale PDEs

  Robert Joseph George, Jiawei Zhao, Jean Kossaifi, Zongyi Li, Anima Anandkumar, September 2024
  [openreview] [pdf] [bib] [code]

• The Real Tropical Geometry of Neural Networks for Binary Classification

  Marie-Charlotte Brandenburg, Georg Loho, Guido Montufar, September 2024
  [openreview] [pdf] [bib]

• Membership Inference Attacks and Privacy in Topic Modeling

  Nico Manzonelli, Wanrong Zhang, Salil Vadhan, September 2024
  [openreview] [pdf] [bib] [code]

• Rethinking Teacher-Student Curriculum Learning through the Cooperative Mechanics of Experience

  Manfred Diaz, Liam Paull, Andrea Tacchetti, September 2024
  [openreview] [pdf] [bib]

• An Attentive Approach for Building Partial Reasoning Agents from Pixels

  Safa Alver, Doina Precup, September 2024
  [openreview] [pdf] [bib]

• Fairness Under Demographic Scarce Regime

  Patrik Joslin Kenfack, Samira Ebrahimi Kahou, Ulrich Aïvodji, September 2024
  [openreview] [pdf] [bib] [code]

• MDP: A Generalized Framework for Text-Guided Image Editing by Manipulating the Diffusion Path

  Qian Wang, Biao Zhang, Michael Birsak, Peter Wonka, September 2024
  [openreview] [pdf] [bib] [code]

• Preconditioned Neural Posterior Estimation for Likelihood-free Inference

  Xiaoyu Wang, Ryan P. Kelly, David J Warne, Christopher Drovandi, September 2024
  [openreview] [pdf] [bib] [code]

• PASS: Pruning Attention Heads with Almost-sure Sparsity Targets

  Dujian Ding, Ganesh Jawahar, Laks V. S. Lakshmanan, September 2024
  [openreview] [pdf] [bib]

• Overcoming the Stability Gap in Continual Learning

  Md Yousuf Harun, Christopher Kanan, September 2024
  [openreview] [pdf] [bib] [code]

• Mitigating Simplicity Bias in Deep Learning for Improved OOD Generalization and Robustness

  Bhavya Vasudeva, Kameron Shahabi, Vatsal Sharan, September 2024
  [openreview] [pdf] [bib] [code]

• A Fisher-Rao gradient flow for entropic mean-field min-max games

  Razvan-Andrei Lascu, Mateusz B. Majka, Lukasz Szpruch, September 2024
  [openreview] [pdf] [bib]

• Unsupervised Domain Adaptation by Learning Using Privileged Information

  Adam Breitholtz, Anton Matsson, Fredrik D. Johansson, September 2024
  [openreview] [pdf] [bib] [code]

• MaskMA: Towards Zero-Shot Multi-Agent Decision Making with Mask-Based Collaborative Learning

  Jie Liu, Yinmin Zhang, Chuming Li, Zhiyuan You, Zhanhui Zhou, Chao Yang, Yaodong Yang, Yu Liu, Wanli Ouyang, September 2024
  [openreview] [pdf] [bib]

• Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code

  Ziyin Zhang, Chaoyu Chen, Bingchang Liu, Cong Liao, Zi Gong, Hang Yu, Jianguo Li, Rui Wang, September 2024
  [openreview] [pdf] [bib] [code]

• Vision Learners Meet Web Image-Text Pairs

  Bingchen Zhao, Quan Cui, Hao Wu, Osamu Yoshie, Cheng Yang, Oisin Mac Aodha, September 2024
  [openreview] [pdf] [bib] [code]

• Pushing the Limits of Gradient Descent for Efficient Learning on Large Images

  Deepak Gupta, Gowreesh Mago, Arnav Chavan, Dilip Prasad, Rajat Mani Thomas, September 2024
  [openreview] [pdf] [bib] [code]

• Multi-Grid Tensorized Fourier Neural Operator for High- Resolution PDEs

  Jean Kossaifi, Nikola Borislavov Kovachki, Kamyar Azizzadenesheli, Anima Anandkumar, September 2024
  [openreview] [pdf] [bib]

• A Greedy Hierarchical Approach to Whole-Network Filter-Pruning in CNNs

  Kiran Purohit, Anurag Reddy Parvathgari, Sourangshu Bhattacharya, September 2024
  [openreview] [pdf] [bib] [code]

• Feedback-guided Data Synthesis for Imbalanced Classification

  Reyhane Askari Hemmat, Mohammad Pezeshki, Florian Bordes, Michal Drozdzal, Adriana Romero-Soriano, September 2024
  [openreview] [pdf] [bib] [code]

• Piecewise-Stationary Dueling Bandits

  Patrick Kolpaczki, Eyke Hüllermeier, Viktor Bengs, September 2024
  [openreview] [pdf] [bib] [code]

• Contrastive Learning with Consistent Representations

  Zihu Wang, Yu Wang, Zhuotong Chen, Hanbin Hu, Peng Li, September 2024
  [openreview] [pdf] [bib] [code]

• Concept-Driven Continual Learning

  Sin-Han Yang, Tuomas Oikarinen, Tsui-Wei Weng, September 2024
  [openreview] [pdf] [bib]

• Multi-intention Inverse Q-learning for Interpretable Behavior Representation

  Hao Zhu, Brice De La Crompe, Gabriel Kalweit, Artur Schneider, Maria Kalweit, Ilka Diester, Joschka Boedecker, September 2024
  [openreview] [pdf] [bib] [code]

• Large Language Models Synergize with Automated Machine Learning

  Jinglue Xu, Jialong Li, Zhen Liu, NAV Suryanarayanan, Guoyuan Zhou, JIA GUO, Hitoshi Iba, Kenji Tei, September 2024
  [openreview] [pdf] [bib] [code]

• Mechanistic Interpretability for AI Safety - A Review

  Leonard Bereska, Stratis Gavves, September 2024
  [openreview] [pdf] [bib]
  Certifications: Survey Written by Expert Reviewer

• Unified Convergence Theory of Stochastic and Variance-Reduced Cubic Newton Methods

  El Mahdi Chayti, Martin Jaggi, Nikita Doikov, September 2024
  [openreview] [pdf] [bib] [code]

• Orthogonal Random Features: Explicit Forms and Sharp Inequalities

  Nizar Demni, Hachem Kadri, September 2024
  [openreview] [pdf] [bib]

• The Kernel Perspective on Dynamic Mode Decomposition

  Efrain Gonzalez, Moad Abudia, Michael Jury, Rushikesh Kamalapurkar, Joel A Rosenfeld, September 2024
  [openreview] [pdf] [bib] [code]

• Graph Structure Learning with Interpretable Bayesian Neural Networks

  Max Wasserman, Gonzalo Mateos, September 2024
  [openreview] [pdf] [bib] [code]

• Sparse Modal Regression with Mode-Invariant Skew Noise

  Kazuki Koyama, Takayuki Kawashima, Hironori Fujisawa, September 2024
  [openreview] [pdf] [bib]

• Boosting Unsupervised Semantic Segmentation with Principal Mask Proposals

  Oliver Hahn, Nikita Araslanov, Simone Schaub-Meyer, Stefan Roth, September 2024
  [openreview] [pdf] [bib] [code]

• Invariance & Causal Representation Learning: Prospects and Limitations

  Simon Bing, Tom Hochsprung, Jonas Wahl, Urmi Ninad, Jakob Runge, September 2024
  [openreview] [pdf] [bib]

• MixedNUTS: Training-Free Accuracy-Robustness Balance via Nonlinearly Mixed Classifiers

  Yatong Bai, Mo Zhou, Vishal M. Patel, Somayeh Sojoudi, September 2024
  [openreview] [pdf] [bib] [code]

• Tabula: Efficiently Computing Nonlinear Activation Functions for Secure Neural Network Inference

  Max Lam, Michael Mitzenmacher, Vijay Janapa Reddi, Gu-Yeon Wei, David Brooks, September 2024
  [openreview] [pdf] [bib] [code]

• Switching Latent Bandits

  Alessio Russo, Alberto Maria Metelli, Marcello Restelli, September 2024
  [openreview] [pdf] [bib] [code]

• A Bag of Tricks for Few-Shot Class-Incremental Learning

  Shuvendu Roy, Chunjong Park, Aldi Fahrezi, Ali Etemad, September 2024
  [openreview] [pdf] [bib]

• Deep Generative Models for Offline Policy Learning: Tutorial, Survey, and Perspectives on Future Directions

  Jiayu Chen, Bhargav Ganguly, Yang Xu, Yongsheng Mei, Tian Lan, Vaneet Aggarwal, September 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Survey

• Probabilistic Matching of Real and Generated Data Statistics in Generative Adversarial Networks

  Philipp Pilar, Niklas Wahlström, September 2024
  [openreview] [pdf] [bib] [code]

• Representation Norm Amplification for Out-of-Distribution Detection in Long-Tail Learning

  Dong Geun Shin, Hye Won Chung, September 2024
  [openreview] [pdf] [bib] [code]

• Oops, I Sampled it Again: Reinterpreting Confidence Intervals in Few-Shot Learning

  Raphael Lafargue, Luke A Smith, Franck VERMET, Matthias Löwe, Ian Reid, Jack Valmadre, Vincent Gripon, September 2024
  [openreview] [pdf] [bib] [code]

• Learning by Self-Explaining

  Wolfgang Stammer, Felix Friedrich, David Steinmann, Manuel Brack, Hikaru Shindo, Kristian Kersting, September 2024
  [openreview] [pdf] [bib] [code]

• Input Normalized Stochastic Gradient Descent Training for Deep Neural Networks

  Salih Furkan Atici, Hongyi Pan, Ahmet Cetin, September 2024
  [openreview] [pdf] [bib] [code]

• Meta Learning for Support Recovery of High-Dimensional Ising Models

  Huiming Xie, Jean Honorio, September 2024
  [openreview] [pdf] [bib]

• TacoGFN: Target-conditioned GFlowNet for Structure-based Drug Design

  Tony Shen, Seonghwan Seo, Grayson Lee, Mohit Pandey, Jason R Smith, Artem Cherkasov, Woo Youn Kim, Martin Ester, September 2024
  [openreview] [pdf] [bib] [code]

• Discriminative reconstruction via simultaneous dense and sparse coding

  Abiy Tasissa, Manos Theodosis, Bahareh Tolooshams, Demba E. Ba, September 2024
  [openreview] [pdf] [bib] [code]

• Reproducibility Study Of Learning Fair Graph Representations Via Automated Data Augmentations

  Thijmen Nijdam, Juell Sprott, Taiki Papandreou-Lazos, Jurgen de Heus, September 2024
  [openreview] [pdf] [bib] [code]

• Structural Pruning of Pre-trained Language Models via Neural Architecture Search

  Aaron Klein, Jacek Golebiowski, Xingchen Ma, Valerio Perrone, Cedric Archambeau, September 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Survey Written by Expert Reviewer

• A Large-Scale 3D Face Mesh Video Dataset via Neural Re-parameterized Optimization

  Kim Youwang, Lee Hyun, Kim Sung-Bin, Suekyeong Nam, Janghoon Ju, Tae-Hyun Oh, September 2024
  [openreview] [pdf] [bib] [code]

• Foundational Challenges in Assuring Alignment and Safety of Large Language Models

  Usman Anwar, Abulhair Saparov, Javier Rando, Daniel Paleka, Miles Turpin, Peter Hase, Ekdeep Singh Lubana, Erik Jenner, Stephen Casper, Oliver Sourbut, Benjamin L. Edelman, Zhaowei Zhang, Mario Günther, Anton Korinek, Jose Hernandez-Orallo, Lewis Hammond, Eric J Bigelow, Alexander Pan, Lauro Langosco, Tomasz Korbak, Heidi Chenyu Zhang, Ruiqi Zhong, Sean O hEigeartaigh, Gabriel Recchia, Giulio Corsi, Alan Chan, Markus Anderljung, Lilian Edwards, Aleksandar Petrov, Christian Schroeder de Witt, Sumeet Ramesh Motwani, Yoshua Bengio, Danqi Chen, Philip Torr, Samuel Albanie, Tegan Maharaj, Jakob Nicolaus Foerster, Florian Tramèr, He He, Atoosa Kasirzadeh, Yejin Choi, David Krueger, September 2024
  [openreview] [pdf] [bib]
  Certifications: Survey Written by Expert Reviewer

• Identifying and Clustering Counter Relationships of Team Compositions in PvP Games for Efficient Balance Analysis

  Chiu-Chou Lin, Yu-Wei Shih, Kuei-Ting Kuo, Yu-Cheng Chen, Chien-Hua Chen, Wei-Chen Chiu, I-Chen Wu, August 2024
  [openreview] [pdf] [bib] [code]

• Perceptual Similarity for Measuring Decision-Making Style and Policy Diversity in Games

  Chiu-Chou Lin, Wei-Chen Chiu, I-Chen Wu, August 2024
  [openreview] [pdf] [bib] [code]

• Equivariant Graph Network Approximations of High-Degree Polynomials for Force Field Prediction

  Zhao Xu, Haiyang Yu, Montgomery Bohde, Shuiwang Ji, August 2024
  [openreview] [pdf] [bib]
  Certifications: Featured

• AdaFlood: Adaptive Flood Regularization

  Wonho Bae, Yi Ren, Mohamed Osama Ahmed, Frederick Tung, Danica J. Sutherland, Gabriel L. Oliveira, August 2024
  [openreview] [pdf] [bib] [code]

• Mitigating Group Bias in Federated Learning: Beyond Local Fairness

  Ganghua Wang, Ali Payani, Myungjin Lee, Ramana Rao Kompella, August 2024
  [openreview] [pdf] [bib]

• A Lennard-Jones Layer for Distribution Normalization

  Mulun Na, Jonathan Klein, Biao Zhang, Wojtek Palubicki, Soren Pirk, Dominik Michels, August 2024
  [openreview] [pdf] [bib]

• Graph Reinforcement Learning for Combinatorial Optimization: A Survey and Unifying Perspective

  Victor-Alexandru Darvariu, Stephen Hailes, Mirco Musolesi, August 2024
  [openreview] [pdf] [bib]
  Certifications: Survey

• Sequential Best-Arm Identification with Application to P300 Speller

  Xin Zhou, Botao Hao, Tor Lattimore, Jian Kang, Lexin Li, August 2024
  [openreview] [pdf] [bib] [code]

• EHI: End-to-end Learning of Hierarchical Index for Efficient Dense Retrieval

  Ramnath Kumar, Anshul Mittal, Nilesh Gupta, Aditya Kusupati, Inderjit S Dhillon, Prateek Jain, August 2024
  [openreview] [pdf] [bib]

• On the Data Heterogeneity in Adaptive Federated Learning

  Yujia Wang, Jinghui Chen, August 2024
  [openreview] [pdf] [bib]

• Discffusion: Discriminative Diffusion Models as Few-shot Vision and Language Learners

  Xuehai He, Weixi Feng, Tsu-Jui Fu, Varun Jampani, Arjun Reddy Akula, Pradyumna Narayana, S Basu, William Yang Wang, Xin Eric Wang, August 2024
  [openreview] [pdf] [bib] [code]

• “Studying How to Efficiently and Effectively Guide Models with Explanations” - A Reproducibility Study

  Adrian Sauter, Milan Miletić, Ryan Ott, Rohith Saai Pemmasani Prabakaran, August 2024
  [openreview] [pdf] [bib] [code]

• PCNN: Probable-Class Nearest-Neighbor Explanations Improve Fine-Grained Image Classification Accuracy for AIs and Humans

  Giang Nguyen, Valerie Chen, Mohammad Reza Taesiri, Anh Totti Nguyen, August 2024
  [openreview] [pdf] [bib]

• Leveraging Task Structures for Improved Identifiability in Neural Network Representations

  Wenlin Chen, Julien Horwood, Juyeon Heo, José Miguel Hernández-Lobato, August 2024
  [openreview] [pdf] [bib] [code]

• Re-Thinking Inverse Graphics With Large Language Models

  Peter Kulits, Haiwen Feng, Weiyang Liu, Victoria Fernandez Abrevaya, Michael J. Black, August 2024
  [openreview] [pdf] [bib] [code]

• Guarantees of confidentiality via Hammersley-Chapman-Robbins bounds

  Kamalika Chaudhuri, Chuan Guo, Laurens van der Maaten, Saeed Mahloujifar, Mark Tygert, August 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility

• Path Development Network with Finite-dimensional Lie Group

  Hang Lou, Siran Li, Hao Ni, August 2024
  [openreview] [pdf] [bib] [code]

• Biased Dueling Bandits with Stochastic Delayed Feedback

  Bongsoo Yi, Yue Kang, Yao Li, August 2024
  [openreview] [pdf] [bib]

• AdaStop: adaptive statistical testing for sound comparisons of Deep RL agents

  Timothée Mathieu, Matheus Medeiros Centa, Riccardo Della Vecchia, Hector Kohler, Alena Shilova, Odalric-Ambrym Maillard, Philippe Preux, August 2024
  [openreview] [pdf] [bib] [code]

• Deconfounding Imitation Learning with Variational Inference

  Risto Vuorio, Pim De Haan, Johann Brehmer, Hanno Ackermann, Daniel Dijkman, Taco Cohen, August 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Robust Feature Inference: A Test-time Defense Strategy using Spectral Projections

  Anurag Singh, Mahalakshmi Sabanayagam, Krikamol Muandet, Debarghya Ghoshdastidar, August 2024
  [openreview] [pdf] [bib] [code]

• A Practical Guide to Sample-based Statistical Distances for Evaluating Generative Models in Science

  Sebastian Bischoff, Alana Darcher, Michael Deistler, Richard Gao, Franziska Gerken, Manuel Gloeckler, Lisa Haxel, Jaivardhan Kapoor, Janne K Lappalainen, Jakob H. Macke, Guy Moss, Matthijs Pals, Felix C Pei, Rachel Rapp, A Erdem Sağtekin, Cornelius Schröder, Auguste Schulz, Zinovia Stefanidi, Shoji Toyota, Linda Ulmer, Julius Vetter, August 2024
  [openreview] [pdf] [bib] [code]

• Learning a Decision Tree Algorithm with Transformers

  Yufan Zhuang, Liyuan Liu, Chandan Singh, Jingbo Shang, Jianfeng Gao, August 2024
  [openreview] [pdf] [bib] [code]

• InvariantStock: Learning Invariant Features for Mastering the Shifting Market

  Haiyao Cao, Jinan Zou, Yuhang Liu, Zhen Zhang, Ehsan Abbasnejad, Anton van den Hengel, Javen Qinfeng Shi, August 2024
  [openreview] [pdf] [bib] [code]

• GCondNet: A Novel Method for Improving Neural Networks on Small High-Dimensional Tabular Data

  Andrei Margeloiu, Nikola Simidjievski, Pietro Lio, Mateja Jamnik, August 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility

• XAI-Based Detection of Adversarial Attacks on Deepfake Detectors

  Ben Pinhasov, Raz Lapid, Rony Ohayon, Moshe Sipper, Yehudit Aperstein, August 2024
  [openreview] [pdf] [bib] [code]

• Robust and Efficient Quantization-aware Training via Coreset Selection

  Xijie Huang, Zechun Liu, Shih-Yang Liu, Kwang-Ting Cheng, August 2024
  [openreview] [pdf] [bib] [code]

• AutoCLIP: Auto-tuning Zero-Shot Classifiers for Vision-Language Models

  Jan Hendrik Metzen, Piyapat Saranrittichai, Chaithanya Kumar Mummadi, August 2024
  [openreview] [pdf] [bib] [code]

• iHyperTime: Interpretable Time Series Generation with Implicit Neural Representations

  Elizabeth Fons, Alejandro Sztrajman, Yousef El-Laham, Andrea Coletta, Alexandros Iosifidis, Svitlana Vyetrenko, August 2024
  [openreview] [pdf] [bib]

• Sensitivity-Aware Amortized Bayesian Inference

  Lasse Elsemüller, Hans Olischläger, Marvin Schmitt, Paul-Christian Bürkner, Ullrich Koethe, Stefan T. Radev, August 2024
  [openreview] [pdf] [bib]

• Automatic Data Curation for Self-Supervised Learning: A Clustering-Based Approach

  Huy V. Vo, Vasil Khalidov, Timothée Darcet, Théo Moutakanni, Nikita Smetanin, Marc Szafraniec, Hugo Touvron, camille couprie, Maxime Oquab, Armand Joulin, Herve Jegou, Patrick Labatut, Piotr Bojanowski, August 2024
  [openreview] [pdf] [bib] [code]

• Byzantine-Resilient Decentralized Multi-Armed Bandits

  Jingxuan Zhu, Alec Koppel, Alvaro Velasquez, Ji Liu, August 2024
  [openreview] [pdf] [bib] [code]

• On the Stochastic (Variance-Reduced) Proximal Gradient Method for Regularized Expected Reward Optimization

  Ling Liang, Haizhao Yang, August 2024
  [openreview] [pdf] [bib]

• Accelerated Deep Active Learning with Graph-based Sub- Sampling

  Dan Kushnir, Shiyun Xu, August 2024
  [openreview] [pdf] [bib]

• Affordable Generative Agents

  Yangbin Yu, Qin Zhang, junyou li, QIANG FU, Deheng Ye, August 2024
  [openreview] [pdf] [bib]

• Vision-Language Dataset Distillation

  Xindi Wu, Byron Zhang, Zhiwei Deng, Olga Russakovsky, August 2024
  [openreview] [pdf] [bib] [code]

• Training-free Graph Neural Networks and the Power of Labels as Features

  Ryoma Sato, August 2024
  [openreview] [pdf] [bib] [code]

• Defending Against Unknown Corrupted Agents: Reinforcement Learning of Adversarially Robust Nash Equilibria

  Andi Nika, Jonathan Nöther, Adish Singla, Goran Radanovic, August 2024
  [openreview] [pdf] [bib]

• C3DM: Constrained-Context Conditional Diffusion Models for Imitation Learning

  Vaibhav Saxena, Yotto koga, Danfei Xu, August 2024
  [openreview] [pdf] [bib]

• Memorisation in Machine Learning: A Survey of Results

  Dmitrii Usynin, Moritz Knolle, Georgios Kaissis, August 2024
  [openreview] [pdf] [bib]

• Privacy-Preserving Split Learning with Vision Transformers using Patch-Wise Random and Noisy CutMix

  Seungeun Oh, Sihun Baek, Jihong Park, Hyelin Nam, Praneeth Vepakomma, Ramesh Raskar, Mehdi Bennis, Seong-Lyun Kim, August 2024
  [openreview] [pdf] [bib]

• Self-Supervised Visual Representation Learning for Medical Image Analysis: A Comprehensive Survey

  Siladittya Manna, Saumik Bhattacharya, Umapada Pal, August 2024
  [openreview] [pdf] [bib]
  Certifications: Survey

• Causal Reasoning and Large Language Models: Opening a New Frontier for Causality

  Emre Kiciman, Robert Ness, Amit Sharma, Chenhao Tan, August 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• APBench: A Unified Availability Poisoning Attack and Defenses Benchmark

  Tianrui Qin, Xitong Gao, Juanjuan Zhao, Kejiang Ye, Cheng-zhong Xu, August 2024
  [openreview] [pdf] [bib] [code]

• DFML: Decentralized Federated Mutual Learning

  Yasser H. Khalil, Amir Hossein Estiri, Mahdi Beitollahi, Nader Asadi, Sobhan Hemati, Xu Li, Guojun Zhang, Xi Chen, August 2024
  [openreview] [pdf] [bib]

• LoRA Learns Less and Forgets Less

  Dan Biderman, Jacob Portes, Jose Javier Gonzalez Ortiz, Mansheej Paul, Philip Greengard, Connor Jennings, Daniel King, Sam Havens, Vitaliy Chiley, Jonathan Frankle, Cody Blakeney, John Patrick Cunningham, August 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• kNN-CLIP: Retrieval Enables Training-Free Segmentation on Continually Expanding Large Vocabularies

  Zhongrui Gui, Shuyang Sun, Runjia Li, Jianhao Yuan, Zhaochong An, Karsten Roth, Ameya Prabhu, Philip Torr, August 2024
  [openreview] [pdf] [bib]

• Revisiting Feature Prediction for Learning Visual Representations from Video

  Adrien Bardes, Quentin Garrido, Jean Ponce, Xinlei Chen, Michael Rabbat, Yann LeCun, Mido Assran, Nicolas Ballas, August 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• Bayesian optimization with derivatives acceleration

  Guillaume Perrin, rodolphe le riche, August 2024
  [openreview] [pdf] [bib]

• Learning $k$-Level Structured Sparse Neural Networks Using Group Envelope Regularization

  Yehonathan Refael, Iftach Arbel, Wasim Huleihel, August 2024
  [openreview] [pdf] [bib]

• Demonstrating and Reducing Shortcuts in Vision-Language Representation Learning

  Maurits Bleeker, Mariya Hendriksen, Andrew Yates, Maarten de Rijke, August 2024
  [openreview] [pdf] [bib] [code]

• Variational Bayesian Imaging with an Efficient Surrogate Score-based Prior

  Berthy Feng, Katherine Bouman, August 2024
  [openreview] [pdf] [bib] [code]

• Differentiating Through Integer Linear Programs with Quadratic Regularization and Davis-Yin Splitting

  Daniel McKenzie, Howard Heaton, Samy Wu Fung, August 2024
  [openreview] [pdf] [bib] [code]

• Calibrating Deep Ensemble through Functional Variational Inference

  Zhijie Deng, Feng Zhou, Jianfei Chen, Guoqiang Wu, Jun Zhu, August 2024
  [openreview] [pdf] [bib] [code]

• Federated Variational Inference: Towards Improved Personalization and Generalization

  Elahe Vedadi, Joshua V. Dillon, Philip Andrew Mansfield, Karan Singhal, Arash Afkanpour, Warren Richard Morningstar, August 2024
  [openreview] [pdf] [bib]

• How to choose the right transfer learning protocol? A qualitative analysis in a controlled set-up

  Federica Gerace, Diego Doimo, Stefano Sarao Mannelli, Luca Saglietti, Alessandro Laio, August 2024
  [openreview] [pdf] [bib]

• Graph Harmony: Denoising and Nuclear-Norm Wasserstein Adaptation for Enhanced Domain Transfer in Graph-Structured Data

  Mengxi Wu, Mohammad Rostami, August 2024
  [openreview] [pdf] [bib]

• Learning Hybrid Interpretable Models: Theory, Taxonomy, and Methods

  Julien Ferry, Gabriel Laberge, Ulrich Aïvodji, August 2024
  [openreview] [pdf] [bib] [code]

• Closing the gap between SVRG and TD-SVRG with Gradient Splitting

  Arsenii Mustafin, Alex Olshevsky, Ioannis Paschalidis, August 2024
  [openreview] [pdf] [bib] [code]

• Finite-Time Analysis of Temporal Difference Learning with Experience Replay

  Han-Dong Lim, Donghwan Lee, August 2024
  [openreview] [pdf] [bib]

• The Cold Posterior Effect Indicates Underfitting, and Cold Posteriors Represent a Fully Bayesian Method to Mitigate It

  Yijie Zhang, Yi-Shan Wu, Luis A. Ortega, Andres R Masegosa, August 2024
  [openreview] [pdf] [bib] [code]

• Meta-Learning Approach for Joint Multimodal Signals with Multimodal Iterative Adaptation

  Sehun Lee, Wonkwang Lee, Gunhee Kim, August 2024
  [openreview] [pdf] [bib] [code]

• Dynamic Structure Estimation from Bandit Feedback using Nonvanishing Exponential Sums

  Motoya Ohnishi, Isao Ishikawa, Yuko Kuroki, Masahiro Ikeda, August 2024
  [openreview] [pdf] [bib] [code]

• Improving Black-box Robustness with In-Context Rewriting

  Kyle O'Brien, Nathan Hoyen Ng, Isha Puri, Jorge Mendez-Mendez, Hamid Palangi, Yoon Kim, Marzyeh Ghassemi, Thomas Hartvigsen, August 2024
  [openreview] [pdf] [bib] [code]

• Efficient Action Robust Reinforcement Learning with Probabilistic Policy Execution Uncertainty

  Guanlin Liu, Zhihan Zhou, Han Liu, Lifeng Lai, August 2024
  [openreview] [pdf] [bib]

• Pre-trained Hypergraph Convolutional Neural Networks with Self-supervised Learning

  Yihe Deng, Ruochi Zhang, Pan Xu, Jian Ma, Quanquan Gu, August 2024
  [openreview] [pdf] [bib] [code]

• Attacking Bayes: On the Adversarial Robustness of Bayesian Neural Networks

  Yunzhen Feng, Tim G. J. Rudner, Nikolaos Tsilivis, Julia Kempe, August 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility

• Variational Autoencoding of Dental Point Clouds

  Johan Ziruo Ye, Thomas Ørkild, Peter Lempel Søndergard, Søren Hauberg, August 2024
  [openreview] [pdf] [bib] [code]

• The Survival Bandit Problem

  Charles Riou, Junya Honda, Masashi Sugiyama, August 2024
  [openreview] [pdf] [bib]

• Improving Predictor Reliability with Selective Recalibration

  Thomas P Zollo, Zhun Deng, Jake Snell, Toniann Pitassi, Richard Zemel, August 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee

  Haoyu Peter Wang, Jialin Liu, Xiaohan Chen, Xinshang Wang, Pan Li, Wotao Yin, July 2024
  [openreview] [pdf] [bib]

• Deep Backtracking Counterfactuals for Causally Compliant Explanations

  Klaus-Rudolf Kladny, Julius von Kügelgen, Bernhard Schölkopf, Michael Muehlebach, July 2024
  [openreview] [pdf] [bib] [code]

• Supervised Domain Adaptation Based on Marginal and Conditional Distributions Alignment

  Ori Katz, Ronen Talmon, Uri Shaham, July 2024
  [openreview] [pdf] [bib]

• Exploiting Hankel-Toeplitz Structures for Fast Computation of Kernel Precision Matrices

  Frida Marie Viset, Anton Kullberg, Frederiek Wesel, Arno Solin, July 2024
  [openreview] [pdf] [bib] [code]

• Doubly Robust Kernel Statistics for Testing Distributional Treatment Effects

  Jake Fawkes, Robert Hu, Robin J. Evans, Dino Sejdinovic, July 2024
  [openreview] [pdf] [bib] [code]

• How to think step-by-step: A mechanistic understanding of chain-of-thought reasoning

  Subhabrata Dutta, Joykirat Singh, Soumen Chakrabarti, Tanmoy Chakraborty, July 2024
  [openreview] [pdf] [bib]

• Weighted Risk Invariance: Domain Generalization under Invariant Feature Shift

  Gina Wong, Joshua Gleason, Rama Chellappa, Yoav Wald, Anqi Liu, July 2024
  [openreview] [pdf] [bib] [code]

• Federated Learning with Reduced Information Leakage and Computation

  Tongxin Yin, Xuwei Tan, Xueru Zhang, Mohammad Mahdi Khalili, Mingyan Liu, July 2024
  [openreview] [pdf] [bib] [code]

• Multi-Fidelity Active Learning with GFlowNets

  Alex Hernández-García, Nikita Saxena, Moksh Jain, Cheng-Hao Liu, Yoshua Bengio, July 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Transformer-Based Models Are Not Yet Perfect At Learning to Emulate Structural Recursion

  Dylan Zhang, Curt Tigges, Zory Zhang, Stella Biderman, Maxim Raginsky, Talia Ringer, July 2024
  [openreview] [pdf] [bib]

• Revisiting Non-separable Binary Classification and its Applications in Anomaly Detection

  Matthew Lau, ISMAILA SECK, Athanasios P Meliopoulos, Wenke Lee, Eugene Ndiaye, July 2024
  [openreview] [pdf] [bib] [code]

• SEAL: Simultaneous Label Hierarchy Exploration And Learning

  Zhiquan Tan, Zihao Wang, Yifan Zhang, July 2024
  [openreview] [pdf] [bib]

• Fast and Effective Weight Update for Pruned Large Language Models

  Vladimír Boža, July 2024
  [openreview] [pdf] [bib] [code]

• A Self-Representation Learning Method for Unsupervised Feature Selection using Feature Space Basis

  Prayag Tiwari, Farid Saberi Movahed, Saeed Karami, Farshad Saberi-Movahed, Jens Lehmann, Sahar Vahdati, July 2024
  [openreview] [pdf] [bib] [code]

• Cost-Sensitive Learning to Defer to Multiple Experts with Workload Constraints

  Jean Vieira Alves, Diogo Leitão, Sérgio Jesus, Marco O. P. Sampaio, Javier Liébana, Pedro Saleiro, Mario A. T. Figueiredo, Pedro Bizarro, July 2024
  [openreview] [pdf] [bib] [code]

• Task-Relevant Feature Selection with Prediction Focused Mixture Models

  Abhishek Sharma, Catherine Zeng, Sanjana Narayanan, Sonali Parbhoo, Roy H. Perlis, Finale Doshi-Velez, July 2024
  [openreview] [pdf] [bib]

• Convergence Analysis and Trajectory Comparison of Gradient Descent for Overparameterized Deep Linear Networks

  Hongru Zhao, Jinchao Xu, July 2024
  [openreview] [pdf] [bib]

• Variational Learning ISTA

  Fabio Valerio Massoli, Christos Louizos, Arash Behboodi, July 2024
  [openreview] [pdf] [bib]

• Correcting Flaws in Common Disentanglement Metrics

  Louis Mahon, Lei Sha, Thomas Lukasiewicz, July 2024
  [openreview] [pdf] [bib] [code]

• Overcoming Order in Autoregressive Graph Generation for Molecule Generation

  Edo Cohen-Karlik, Eyal Rozenberg, Daniel Freedman, July 2024
  [openreview] [pdf] [bib]

• Neural Clamping: Joint Input Perturbation and Temperature Scaling for Neural Network Calibration

  Yung-Chen Tang, Pin-Yu Chen, Tsung-Yi Ho, July 2024
  [openreview] [pdf] [bib] [code]

• A replica analysis of under-bagging

  Takashi Takahashi, July 2024
  [openreview] [pdf] [bib]

• Augment then Smooth: Reconciling Differential Privacy with Certified Robustness

  Jiapeng Wu, Atiyeh Ashari Ghomi, David Glukhov, Jesse C. Cresswell, Franziska Boenisch, Nicolas Papernot, July 2024
  [openreview] [pdf] [bib] [code]

• Deep Unlearning: Fast and Efficient Gradient-free Class Forgetting

  Sangamesh Kodge, Gobinda Saha, Kaushik Roy, July 2024
  [openreview] [pdf] [bib] [code]

• Dual-windowed Vision Transformer with Angular Self- Attention

  Weili Shi, Sheng Li, July 2024
  [openreview] [pdf] [bib] [code]

• On the Importance of Uncertainty in Decision-Making with Large Language Models

  Nicolò Felicioni, Lucas Maystre, Sina Ghiassian, Kamil Ciosek, July 2024
  [openreview] [pdf] [bib]

• ITEM: Improving Training and Evaluation of Message-Passing based GNNs for top-k recommendation

  Yannis Karmim, Elias Ramzi, Raphael Fournier-S'niehotta, Nicolas THOME, July 2024
  [openreview] [pdf] [bib]

• Interpreting Global Perturbation Robustness of Image Models using Axiomatic Spectral Importance Decomposition

  Roisin Luo, James McDermott, Colm O'Riordan, July 2024
  [openreview] [pdf] [bib] [code]

• DeepReShape: Redesigning Neural Networks for Efficient Private Inference

  Nandan Kumar Jha, Brandon Reagen, July 2024
  [openreview] [pdf] [bib] [code]

• Exploiting Edge Features in Graph-based Learning with Fused Network Gromov-Wasserstein Distance

  Junjie Yang, Matthieu Labeau, Florence d'Alché-Buc, July 2024
  [openreview] [pdf] [bib] [code]

• Mini-Batch Optimization of Contrastive Loss

  Jaewoong Cho, Kartik Sreenivasan, Keon Lee, Kyunghoo Mun, Soheun Yi, Jeong-Gwan Lee, Anna Lee, Jy-yong Sohn, Dimitris Papailiopoulos, Kangwook Lee, July 2024
  [openreview] [pdf] [bib] [code]

• Improved motif-scaffolding with SE(3) flow matching

  Jason Yim, Andrew Campbell, Emile Mathieu, Andrew Y. K. Foong, Michael Gastegger, Jose Jimenez-Luna, Sarah Lewis, Victor Garcia Satorras, Bastiaan S. Veeling, Frank Noe, Regina Barzilay, Tommi Jaakkola, July 2024
  [openreview] [pdf] [bib] [code]

• XAudit : A Learning-Theoretic Look at Auditing with Explanations

  Chhavi Yadav, Michal Moshkovitz, Kamalika Chaudhuri, July 2024
  [openreview] [pdf] [bib]

• Fair Representation in Submodular Subset Selection: A Pareto Optimization Approach

  Adriano Fazzone, Yanhao Wang, Francesco Bonchi, July 2024
  [openreview] [pdf] [bib] [code]

• Representation Learning Dynamics of Self-Supervised Models

  Pascal Esser, Satyaki Mukherjee, Debarghya Ghoshdastidar, July 2024
  [openreview] [pdf] [bib]

• Learning Counterfactually Invariant Predictors

  Francesco Quinzan, Cecilia Casolo, Krikamol Muandet, Yucen Luo, Niki Kilbertus, July 2024
  [openreview] [pdf] [bib] [code]

• A Note on the Convergence of Denoising Diffusion Probabilistic Models

  Sokhna Diarra Mbacke, Omar Rivasplata, July 2024
  [openreview] [pdf] [bib]

• Data Attribution for Diffusion Models: Timestep-induced Bias in Influence Estimation

  Tong Xie, Haoyu Li, Andrew Bai, Cho-Jui Hsieh, July 2024
  [openreview] [pdf] [bib] [code]

• Language Models Are Better Than Humans at Next-token Prediction

  Buck Shlegeris, Fabien Roger, Lawrence Chan, Euan McLean, July 2024
  [openreview] [pdf] [bib] [code]

• Vision-Language Instruction Tuning: A Review and Analysis

  Chen Li, Yixiao Ge, Dian Li, Ying Shan, July 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Survey

• Harnessing the Power of Federated Learning in Federated Contextual Bandits

  Chengshuai Shi, Ruida Zhou, Kun Yang, Cong Shen, July 2024
  [openreview] [pdf] [bib] [code]

• Diversity-Preserving $K$--Armed Bandits, Revisited

  Hedi Hadiji, Sébastien Gerchinovitz, Jean-Michel Loubes, Gilles Stoltz, July 2024
  [openreview] [pdf] [bib] [code]

• Masked multi-prediction for multi-aspect anomaly detection

  Yassine Naji, Romaric Audigier, Aleksandr Setkov, Angelique Loesch, Michèle Gouiffès, July 2024
  [openreview] [pdf] [bib]

• A Survey on Data Selection for Language Models

  Alon Albalak, Yanai Elazar, Sang Michael Xie, Shayne Longpre, Nathan Lambert, Xinyi Wang, Niklas Muennighoff, Bairu Hou, Liangming Pan, Haewon Jeong, Colin Raffel, Shiyu Chang, Tatsunori Hashimoto, William Yang Wang, July 2024
  [openreview] [pdf] [bib]
  Certifications: Survey

• Read Between the Layers: Leveraging Multi-Layer Representations for Rehearsal-Free Continual Learning with Pre-Trained Models

  Kyra Ahrens, Hans Hergen Lehmann, Jae Hee Lee, Stefan Wermter, July 2024
  [openreview] [pdf] [bib] [code]

• Reproducibility Study: Equal Improvability: A New Fairness Notion Considering the Long-Term Impact

  Berkay Chakar, Amina Izbassar, Mina Janićijević, Jakub Tomaszewski, July 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility Event: reproml.org/MLRC/2023/Journal_Track

• SeqLink: A Robust Neural-ODE Architecture for Modelling Partially Observed Time Series

  Futoon M. Abushaqra, Hao Xue, Yongli Ren, Flora D. Salim, July 2024
  [openreview] [pdf] [bib] [code]

• Incorporating Unlabelled Data into Bayesian Neural Networks

  Mrinank Sharma, Tom Rainforth, Yee Whye Teh, Vincent Fortuin, July 2024
  [openreview] [pdf] [bib]
  Certifications: Written by Expert Reviewer

• XPL: A Cross-Model framework for Semi-Supervised Prompt Learning in Vision-Language Models

  Omprakash Chakraborty, Aadarsh Sahoo, Rameswar Panda, Abir Das, July 2024
  [openreview] [pdf] [bib] [code]

• Revisiting Active Learning in the Era of Vision Foundation Models

  Sanket Rajan Gupte, Josiah Aklilu, Jeffrey J Nirschl, Serena Yeung-Levy, July 2024
  [openreview] [pdf] [bib] [code]

• CompoDiff: Versatile Composed Image Retrieval With Latent Diffusion

  Geonmo Gu, Sanghyuk Chun, Wonjae Kim, HeeJae Jun, Yoohoon Kang, Sangdoo Yun, July 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Homogenizing Non-IID Datasets via In-Distribution Knowledge Distillation for Decentralized Learning

  Deepak Ravikumar, Gobinda Saha, Sai Aparna Aketi, Kaushik Roy, July 2024
  [openreview] [pdf] [bib] [code]

• Combine and Conquer: A Meta-Analysis on Data Shift and Out-of-Distribution Detection

  Eduardo Dadalto Câmara Gomes, Florence Alberge, Pierre Duhamel, Pablo Piantanida, July 2024
  [openreview] [pdf] [bib] [code]

• Directed Graph Transformers

  Qitong Wang, Georgios Kollias, Vasileios Kalantzis, Naoki Abe, Mohammed J Zaki, July 2024
  [openreview] [pdf] [bib] [code]

• Contextual Policies Enable Efficient and Interpretable Inverse Reinforcement Learning for Populations

  Ville Tanskanen, Chang Rajani, Perttu Hämäläinen, Christian Guckelsberger, Arto Klami, July 2024
  [openreview] [pdf] [bib]

• NuTime: Numerically Multi-Scaled Embedding for Large- Scale Time-Series Pretraining

  Chenguo Lin, Xumeng Wen, Wei Cao, Congrui Huang, Jiang Bian, Stephen Lin, Zhirong Wu, July 2024
  [openreview] [pdf] [bib]

• Intriguing Properties of Hyperbolic Embeddings in Vision-Language Models

  Sarah Ibrahimi, Mina Ghadimi Atigh, Nanne Van Noord, Pascal Mettes, Marcel Worring, July 2024
  [openreview] [pdf] [bib] [code]

• Lyra: Orchestrating Dual Correction in Automated Theorem Proving

  Chuanyang Zheng, Haiming Wang, Enze Xie, Zhengying Liu, Jiankai Sun, Huajian Xin, Jianhao Shen, Zhenguo Li, Yu Li, July 2024
  [openreview] [pdf] [bib]

• Understanding the Role of Invariance in Transfer Learning

  Till Speicher, Vedant Nanda, Krishna P. Gummadi, July 2024
  [openreview] [pdf] [bib] [code]

• Jigsaw Game: Federated Clustering

  JINXUAN XU, Hong-You Chen, Wei-Lun Chao, Yuqian Zhang, July 2024
  [openreview] [pdf] [bib]

• Fast, accurate and lightweight sequential simulation-based inference using Gaussian locally linear mappings

  Henrik Häggström, Pedro L. C. Rodrigues, Geoffroy Oudoumanessah, Florence Forbes, Umberto Picchini, July 2024
  [openreview] [pdf] [bib] [code]

• SPriFed-OMP: A Differentially Private Federated Learning Algorithm for Sparse Basis Recovery

  Ajinkya K Mulay, Xiaojun Lin, July 2024
  [openreview] [pdf] [bib]

• Active Sequential Two-Sample Testing

  Weizhi Li, Prad Kadambi, Pouria Saidi, Karthikeyan Natesan Ramamurthy, Gautam Dasarathy, Visar Berisha, July 2024
  [openreview] [pdf] [bib] [code]

• Simple and Scalable Strategies to Continually Pre-train Large Language Models

  Adam Ibrahim, Benjamin Thérien, Kshitij Gupta, Mats Leon Richter, Quentin Gregory Anthony, Eugene Belilovsky, Timothée Lesort, Irina Rish, July 2024
  [openreview] [pdf] [bib] [code]

• Grid Cell-Inspired Fragmentation and Recall for Efficient Map Building

  Jaedong Hwang, Zhang-Wei Hong, Eric R Chen, Akhilan Boopathy, Pulkit Agrawal, Ila R Fiete, July 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• Sparse Contextual CDF Regression

  Kamyar Azizzadenesheli, William Lu, Anuran Makur, Qian Zhang, July 2024
  [openreview] [pdf] [bib] [code]

• D3: Data Diversity Design for Systematic Generalization in Visual Question Answering

  Amir Rahimi, Vanessa D'Amario, Moyuru Yamada, Kentaro Takemoto, Tomotake Sasaki, Xavier Boix, July 2024
  [openreview] [pdf] [bib] [code]

• Decoupling Pixel Flipping and Occlusion Strategy for Consistent XAI Benchmarks

  Stefan Bluecher, Johanna Vielhaben, Nils Strodthoff, July 2024
  [openreview] [pdf] [bib] [code]

• Chain-of-Thought Unfaithfulness as Disguised Accuracy

  Oliver Bentham, Nathan Stringham, Ana Marasovic, July 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility Event: reproml.org/MLRC/2023/Journal_Track

• PRD: Peer Rank and Discussion Improve Large Language Model based Evaluations

  Ruosen Li, Teerth Patel, Xinya Du, July 2024
  [openreview] [pdf] [bib]

• BaSIS-Net: From Point Estimate to Predictive Distribution in Neural Networks - A Bayesian Sequential Importance Sampling Framework

  Giuseppina Carannante, Nidhal Bouaynaya, Ghulam Rasool, Lyudmila Mihaylova, July 2024
  [openreview] [pdf] [bib] [code]

• Object-Centric Relational Representations for Image Generation

  Luca Butera, Andrea Cini, Alberto Ferrante, Cesare Alippi, July 2024
  [openreview] [pdf] [bib] [code]

• A General-Purpose Multi-Modal OOD Detection Framework

  Viet Quoc Duong, Qiong Wu, Zhengyi Zhou, Eric Zavesky, WenLing Hsu, Han Zhao, Huajie Shao, July 2024
  [openreview] [pdf] [bib]

• Federated TD Learning with Linear Function Approximation under Environmental Heterogeneity

  Han Wang, Aritra Mitra, Hamed Hassani, George J. Pappas, James Anderson, July 2024
  [openreview] [pdf] [bib]

• ConsistI2V: Enhancing Visual Consistency for Image-to-Video Generation

  Weiming Ren, Huan Yang, Ge Zhang, Cong Wei, Xinrun Du, Wenhao Huang, Wenhu Chen, July 2024
  [openreview] [pdf] [bib] [code]

• Variational excess risk bound for general state space models

  Elisabeth Gassiat, Sylvain Le Corff, July 2024
  [openreview] [pdf] [bib]

• [Re] Classwise-Shapley values for data valuation

  Markus Semmler, Miguel de Benito Delgado, July 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility Event: reproml.org/MLRC/2023/Journal_Track

• $\sigma$-PCA: a building block for neural learning of identifiable linear transformations

  Fahdi Kanavati, Lucy Katsnith, Masayuki Tsuneki, June 2024
  [openreview] [pdf] [bib] [code]

• Bytes Are All You Need: Transformers Operating Directly On File Bytes

  Maxwell Horton, Sachin Mehta, Ali Farhadi, Mohammad Rastegari, June 2024
  [openreview] [pdf] [bib] [code]

• Fine-tuning can cripple your foundation model; preserving features may be the solution

  Jishnu Mukhoti, Yarin Gal, Philip Torr, Puneet K. Dokania, June 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• Unmasking the Veil: An Investigation into Concept Ablation for Privacy and Copyright Protection in Images

  Shivank Garg, Manyana Tiwari, June 2024
  [openreview] [pdf] [bib]
  Certifications: Event: reproml.org/MLRC/2023/Journal_Track

• Improving Variational Autoencoder Estimation from Incomplete Data with Mixture Variational Families

  Vaidotas Simkus, Michael U. Gutmann, June 2024
  [openreview] [pdf] [bib] [code]

• Conciliator steering: Imposing user preference in multi-objective reinforcement learning

  Sara Pyykölä, Klavdiya Olegovna Bochenina, Laura Ruotsalainen, June 2024
  [openreview] [pdf] [bib] [code]

• Can LLMs Effectively Leverage Graph Structural Information through Prompts, and Why?

  Jin Huang, Xingjian Zhang, Qiaozhu Mei, Jiaqi Ma, June 2024
  [openreview] [pdf] [bib] [code]

• Solving Robust MDPs through No-Regret Dynamics

  Etash Kumar Guha, June 2024
  [openreview] [pdf] [bib]

• Fair Feature Importance Scores for Interpreting Decision Trees

  Camille Olivia Little, Debolina Halder Lina, Genevera I. Allen, June 2024
  [openreview] [pdf] [bib] [code]

• Todyformer: Towards Holistic Dynamic Graph Transformers with Structure-Aware Tokenization

  Mahdi Biparva, Raika Karimi, Faezeh Faez, Yingxue Zhang, June 2024
  [openreview] [pdf] [bib]

• The Disagreement Problem in Explainable Machine Learning: A Practitioner’s Perspective

  Satyapriya Krishna, Tessa Han, Alex Gu, Steven Wu, Shahin Jabbari, Himabindu Lakkaraju, June 2024
  [openreview] [pdf] [bib] [code]

• Choosing the parameter of the Fermat distance: navigating geometry and noise

  Frederic Chazal, Laure Ferraris, Pablo Groisman, Matthieu Jonckheere, Frederic Pascal, Facundo Fabián Sapienza, June 2024
  [openreview] [pdf] [bib]

• On the Unreasonable Effectiveness of Federated Averaging with Heterogeneous Data

  Jianyu Wang, Rudrajit Das, Gauri Joshi, Satyen Kale, Zheng Xu, Tong Zhang, June 2024
  [openreview] [pdf] [bib]

• Reproducibility Study of "ITI-GEN: Inclusive Text-to-Image Generation"

  Daniel Gallo Fernández, Răzvan-Andrei Matișan, Alejandro Monroy Muñoz, Janusz Partyka, June 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Event: reproml.org/MLRC/2023/Journal_Track

• On the Reproducibility of: "Learning Perturbations to Explain Time Series Predictions"

  Wouter Bant, Ádám Divák, Jasper Eppink, Floris Six Dijkstra, June 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility Event: reproml.org/MLRC/2023/Journal_Track

• Revealing an Overlooked Challenge in Class-Incremental Graph Learning

  Daiqing Qi, Handong Zhao, Xiaowei Jia, Sheng Li, June 2024
  [openreview] [pdf] [bib]

• Selective Pre-training for Private Fine-tuning

  Da Yu, Sivakanth Gopi, Janardhan Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang, June 2024
  [openreview] [pdf] [bib] [code]

• Learning Tree-Structured Composition of Data Augmentation

  Dongyue Li, Kailai Chen, Predrag Radivojac, Hongyang R. Zhang, June 2024
  [openreview] [pdf] [bib] [code]

• Large Language Models (LLMs) on Tabular Data: Prediction, Generation, and Understanding - A Survey

  Xi Fang, Weijie Xu, Fiona Anting Tan, Ziqing Hu, Jiani Zhang, Yanjun Qi, Srinivasan H. Sengamedu, Christos Faloutsos, June 2024
  [openreview] [pdf] [bib] [code]

• Koopman Spectrum Nonlinear Regulators and Efficient Online Learning

  Motoya Ohnishi, Isao Ishikawa, Kendall Lowrey, Masahiro Ikeda, Sham M. Kakade, Yoshinobu Kawahara, June 2024
  [openreview] [pdf] [bib] [code]

• Accurate Neural Network Pruning Requires Rethinking Sparse Optimization

  Denis Kuznedelev, Eldar Kurtic, Eugenia Iofinova, Elias Frantar, Alexandra Peste, Dan Alistarh, June 2024
  [openreview] [pdf] [bib]

• Learning Network Granger causality using Graph Prior Knowledge

  Lucas Zoroddu, Pierre Humbert, Laurent Oudre, June 2024
  [openreview] [pdf] [bib]

• Best-of-Both-Worlds Linear Contextual Bandits

  Masahiro Kato, Shinji Ito, June 2024
  [openreview] [pdf] [bib]

• Spike Accumulation Forwarding for Effective Training of Spiking Neural Networks

  Ryuji Saiin, Tomoya Shirakawa, Sota Yoshihara, Yoshihide Sawada, Hiroyuki Kusumoto, June 2024
  [openreview] [pdf] [bib]

• Learning the essential in less than 2k additional weights - a simple approach to improve image classification stability under corruptions

  Kai Bäuerle, Patrick Müller, Syed Muhammad Kazim, Ivo Ihrke, Margret Keuper, June 2024
  [openreview] [pdf] [bib]

• Training-free linear image inverses via flows

  Ashwini Pokle, Matthew J. Muckley, Ricky T. Q. Chen, Brian Karrer, June 2024
  [openreview] [pdf] [bib]

• Towards Unbiased Calibration using Meta-Regularization

  Cheng Wang, Jacek Golebiowski, June 2024
  [openreview] [pdf] [bib]

• Layerwise complexity-matched learning yields an improved model of cortical area V2

  Nikhil Parthasarathy, Olivier J Henaff, Eero P Simoncelli, June 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks

  Rui-Jie Zhu, Qihang Zhao, Guoqi Li, Jason Eshraghian, June 2024
  [openreview] [pdf] [bib] [code]

• Cooperative Online Learning with Feedback Graphs

  Nicolò Cesa-Bianchi, Tommaso Cesari, Riccardo Della Vecchia, June 2024
  [openreview] [pdf] [bib]

• On the numerical reliability of nonsmooth autodiff: a MaxPool case study

  Ryan Boustany, June 2024
  [openreview] [pdf] [bib] [code]

• Universal Neurons in GPT2 Language Models

  Wes Gurnee, Theo Horsley, Zifan Carl Guo, Tara Rezaei Kheirkhah, Qinyi Sun, Will Hathaway, Neel Nanda, Dimitris Bertsimas, June 2024
  [openreview] [pdf] [bib] [code]

• Generalized Oversampling for Learning from Imbalanced datasets and Associated Theory: Application in Regression

  Samuel Stocksieker, Denys Pommeret, Arthur Charpentier, June 2024
  [openreview] [pdf] [bib] [code]

• SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation

  Qi Yan, Zhengyang Liang, Yang Song, Renjie Liao, Lele Wang, June 2024
  [openreview] [pdf] [bib] [code]

• Bit-by-Bit: Investigating the Vulnerabilities of Binary Neural Networks to Adversarial Bit Flipping

  Shamik Kundu, Sanjay Das, Sayar Karmakar, Arnab Raha, Souvik Kundu, Yiorgos Makris, Kanad Basu, June 2024
  [openreview] [pdf] [bib]

• Directional Convergence Near Small Initializations and Saddles in Two-Homogeneous Neural Networks

  Akshay Kumar, Jarvis Haupt, June 2024
  [openreview] [pdf] [bib]

• Towards Minimal Targeted Updates of Language Models with Targeted Negative Training

  Lily H Zhang, Rajesh Ranganath, Arya Tafvizi, June 2024
  [openreview] [pdf] [bib] [code]

• Towards Understanding Variants of Invariant Risk Minimization through the Lens of Calibration

  Kotaro Yoshida, Hiroki Naganuma, June 2024
  [openreview] [pdf] [bib] [code]

• Reproducibility study of "Robust Fair Clustering: A Novel Fairness Attack and Defense Framework"

  Lucas Ponticelli, Vincent Loos, Eren Kocadag, Kacper Bartosik, June 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility Event: reproml.org/MLRC/2023/Journal_Track

• TAP: The Attention Patch for Cross-Modal Knowledge Transfer from Unlabeled Modality

  Yinsong Wang, Shahin Shahrampour, June 2024
  [openreview] [pdf] [bib] [code]

• Mildly Constrained Evaluation Policy for Offline Reinforcement Learning

  Linjie Xu, zhengyao jiang, Jinyu Wang, Lei Song, Jiang Bian, June 2024
  [openreview] [pdf] [bib] [code]

• Deep End-to-end Causal Inference

  Tomas Geffner, Javier Antoran, Adam Foster, Wenbo Gong, Chao Ma, Emre Kiciman, Amit Sharma, Angus Lamb, Martin Kukla, Nick Pawlowski, Agrin Hilmkil, Joel Jennings, Meyer Scetbon, Miltiadis Allamanis, Cheng Zhang, June 2024
  [openreview] [pdf] [bib] [code]

• A Survey on Fairness Without Demographics

  Patrik Joslin Kenfack, Samira Ebrahimi Kahou, Ulrich Aïvodji, June 2024
  [openreview] [pdf] [bib]

• Reproducibility study of FairAC

  Gijs de Jong, Macha J. Meijer, Derck W. E. Prinzhorn, Harold Ruiter, June 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Event: reproml.org/MLRC/2023/Journal_Track

• Multiple Kronecker RLS fusion-based link propagation for drug-side effect prediction

  Yuqing Qian, Ziyu Zheng, Prayag Tiwari, Yijie Ding, Quan Zou, June 2024
  [openreview] [pdf] [bib] [code]

• Knowledge Accumulation in Continually Learned Representations and the Issue of Feature Forgetting

  Timm Hess, Eli Verwimp, Gido M van de Ven, Tinne Tuytelaars, June 2024
  [openreview] [pdf] [bib] [code]

• Gradient Scarcity in Graph Learning with Bilevel Optimization

  Hashem Ghanem, Samuel Vaiter, Nicolas Keriven, June 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• Estimating class separability of text embeddings with persistent homology.

  Kostis Gourgoulias, Najah Ghalyan, Maxime Labonne, yash satsangi, Sean Moran, Joseph Sabelja, June 2024
  [openreview] [pdf] [bib]

• Exploring validation metrics for offline model-based optimisation with diffusion models

  Christopher Beckham, Alexandre Piché, David Vazquez, Christopher Pal, June 2024
  [openreview] [pdf] [bib] [code]

• Solving the Tree Containment Problem Using Graph Neural Networks

  Arkadiy Dushatskiy, Esther Julien, Leen Stougie, Leo van Iersel, June 2024
  [openreview] [pdf] [bib] [code]

• A Simple Video Segmenter by Tracking Objects Along Axial Trajectories

  Ju He, Qihang Yu, Inkyu Shin, Xueqing Deng, Alan Yuille, Xiaohui Shen, Liang-Chieh Chen, June 2024
  [openreview] [pdf] [bib] [code]

• Targeted Active Learning for Bayesian Decision-Making

  Louis Filstroff, Iiris Sundin, Petrus Mikkola, Aleksei Tiulpin, Juuso Kylmäoja, Samuel Kaski, June 2024
  [openreview] [pdf] [bib]

• Q-Learning for Stochastic Control under General Information Structures and Non-Markovian Environments

  Ali Devran Kara, Serdar Yuksel, June 2024
  [openreview] [pdf] [bib]
  Certifications: Featured

• ***FastDoc***: Domain-Specific Fast Continual Pre-training Technique using Document-Level Metadata and Taxonomy

  Abhilash Nandy, Manav Nitin Kapadnis, Sohan Patnaik, Yash Parag Butala, Pawan Goyal, Niloy Ganguly, June 2024
  [openreview] [pdf] [bib] [code]

• Self-Improvement for Neural Combinatorial Optimization: Sample Without Replacement, but Improvement

  Jonathan Pirnay, Dominik G. Grimm, June 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• Smoothed Robustness Analysis: Bridging worst- and average-case robustness analyses via smoothed analysis

  Thomas Rodrigues Crespo, Jun-nosuke Teramae, June 2024
  [openreview] [pdf] [bib] [code]

• [Re] CUDA: Curriculum of Data Augmentation for Long‐tailed Recognition

  Barath Chandran.C, June 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Event: reproml.org/MLRC/2023/Journal_Track

• Hybrid Active Learning with Uncertainty-Weighted Embeddings

  Yinan He, Lile Cai, Jingyi Liao, Chuan-Sheng Foo, June 2024
  [openreview] [pdf] [bib] [code]

• Nuisances via Negativa: Adjusting for Spurious Correlations via Data Augmentation

  Aahlad Manas Puli, Nitish Joshi, Yoav Wald, He He, Rajesh Ranganath, June 2024
  [openreview] [pdf] [bib]

• Making Translators Privacy-aware on the User's Side

  Ryoma Sato, June 2024
  [openreview] [pdf] [bib] [code]

• Convergences for Minimax Optimization Problems over Infinite-Dimensional Spaces Towards Stability in Adversarial Training

  Takashi Furuya, Satoshi Okuda, Kazuma Suetake, Yoshihide Sawada, June 2024
  [openreview] [pdf] [bib]

• CoMIX: A Multi-agent Reinforcement Learning Training Architecture for Efficient Decentralized Coordination and Independent Decision-Making

  Giovanni Minelli, Mirco Musolesi, June 2024
  [openreview] [pdf] [bib] [code]

• [Re] Reproducibility Study of “Explaining Temporal Graph Models Through an Explorer-Navigator Framework"

  Helia Ghasemi, Christina Isaicu, Jesse Wonnink, Andreas Berentzen, June 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Event: reproml.org/MLRC/2023/Journal_Track

• Achieving the Asymptotically Minimax Optimal Sample Complexity of Offline Reinforcement Learning: A DRO-Based Approach

  Yue Wang, Jinjun Xiong, Shaofeng Zou, June 2024
  [openreview] [pdf] [bib]

• Promoting Exploration in Memory-Augmented Adam using Critical Momenta

  Pranshu Malviya, Goncalo Mordido, Aristide Baratin, Reza Babanezhad Harikandeh, Jerry Huang, Simon Lacoste-Julien, Razvan Pascanu, Sarath Chandar, June 2024
  [openreview] [pdf] [bib]

• Physics Informed Distillation for Diffusion Models

  Joshua Tian Jin Tee, Kang Zhang, Hee Suk Yoon, Dhananjaya Nagaraja Gowda, Chanwoo Kim, Chang D. Yoo, June 2024
  [openreview] [pdf] [bib]

• Understanding and Improving Transfer Learning of Deep Models via Neural Collapse

  Xiao Li, Sheng Liu, Jinxin Zhou, Xinyu Lu, Carlos Fernandez-Granda, Zhihui Zhu, Qing Qu, June 2024
  [openreview] [pdf] [bib]

• AGALE: A Graph-Aware Continual Learning Evaluation Framework

  Tianqi Zhao, Alan Hanjalic, Megha Khosla, June 2024
  [openreview] [pdf] [bib]

• VisionAD, a software package of performant anomaly detection algorithms, and Proportion Localised, an interpretable metric

  Alexander D. J. Taylor, Phillip Tregidgo, Jonathan James Morrison, Neill D. F. Campbell, June 2024
  [openreview] [pdf] [bib] [code]

• Holistic Molecular Representation Learning via Multi-view Fragmentation

  Seojin Kim, Jaehyun Nam, Junsu Kim, Hankook Lee, Sungsoo Ahn, Jinwoo Shin, June 2024
  [openreview] [pdf] [bib] [code]

• Recent Link Classification on Temporal Graphs Using Graph Profiler

  Muberra Ozmen, Thomas Markovich, June 2024
  [openreview] [pdf] [bib]

• Hyperbolic Random Forests

  Lars Doorenbos, Pablo Márquez Neila, Raphael Sznitman, Pascal Mettes, June 2024
  [openreview] [pdf] [bib] [code]

• [Re] GNNInterpreter: A probabilistic generative model-level explanation for Graph Neural Networks

  Ana Vasilcoiu, T.H.F. Stessen, Thies Kersten, Batu Helvacioglu, June 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Event: reproml.org/MLRC/2023/Journal_Track

• Distributionally Robust Policy Evaluation under General Covariate Shift in Contextual Bandits

  Yihong Guo, Hao Liu, Yisong Yue, Anqi Liu, June 2024
  [openreview] [pdf] [bib] [code]

• Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference

  Ryan P. Kelly, David J Nott, David Tyler Frazier, David J Warne, Christopher Drovandi, June 2024
  [openreview] [pdf] [bib] [code]

• Rotate the ReLU to Sparsify Deep Networks Implicitly

  Nancy Nayak, Sheetal Kalyani, June 2024
  [openreview] [pdf] [bib] [code]

• Bayesian Quantification with Black-Box Estimators

  Albert Ziegler, Paweł Czyż, June 2024
  [openreview] [pdf] [bib] [code]

• Linear Bandits with Memory

  Giulia Clerici, Pierre Laforgue, Nicolò Cesa-Bianchi, June 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• Simple Imputation Rules for Prediction with Missing Data: Theoretical Guarantees vs. Empirical Performance

  Dimitris Bertsimas, Arthur Delarue, Jean Pauphilet, June 2024
  [openreview] [pdf] [bib] [code]

• DIGNet: Learning Decomposed Patterns in Representation Balancing for Treatment Effect Estimation

  Yiyan HUANG, WANG Siyi, Cheuk Hang LEUNG, Qi WU, Dongdong WANG, Zhixiang Huang, June 2024
  [openreview] [pdf] [bib]

• Mildly Overparameterized ReLU Networks Have a Favorable Loss Landscape

  Kedar Karhadkar, Michael Murray, Hanna Tseran, Guido Montufar, June 2024
  [openreview] [pdf] [bib] [code]

• Augmenting Ad-Hoc IR Dataset for Interactive Conversational Search

  Pierre ERBACHER, Jian-Yun Nie, Philippe Preux, Laure Soulier, June 2024
  [openreview] [pdf] [bib]

• Text Descriptions are Compressive and Invariant Representations for Visual Learning

  Zhili Feng, Anna Bair, J Zico Kolter, June 2024
  [openreview] [pdf] [bib]

• Semi-Supervised Semantic Segmentation via Marginal Contextual Information

  Moshe Kimhi, Shai Kimhi, Evgenii Zheltonozhskii, Or Litany, Chaim Baskin, June 2024
  [openreview] [pdf] [bib]

• Multimodal Chain-of-Thought Reasoning in Language Models

  Zhuosheng Zhang, Aston Zhang, Mu Li, hai zhao, George Karypis, Alex Smola, June 2024
  [openreview] [pdf] [bib] [code]

• Contrastive Graph Autoencoder for Shape-based Polygon Retrieval from Large Geometry Datasets

  Zexian Huang, Kourosh Khoshelham, Martin Tomko, June 2024
  [openreview] [pdf] [bib] [code]

• Prototypical Self-Explainable Models Without Re-training

  Srishti Gautam, Ahcene Boubekki, Marina MC Höhne, Michael Kampffmeyer, June 2024
  [openreview] [pdf] [bib] [code]

• Conservative Prediction via Data-Driven Confidence Minimization

  Caroline Choi, Fahim Tajwar, Yoonho Lee, Huaxiu Yao, Ananya Kumar, Chelsea Finn, June 2024
  [openreview] [pdf] [bib]

• Physical Reasoning and Object Planning for Household Embodied Agents

  Ayush Agrawal, Raghav Prabhakar, Anirudh Goyal, Dianbo Liu, June 2024
  [openreview] [pdf] [bib] [code]

• Reproducibility study of “LICO: Explainable Models with Language-Image Consistency"

  Luan Fletcher, Robert van der Klis, Martin Sedláček, Stefan Vasilev, Christos Athanasiadis, June 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility Event: reproml.org/MLRC/2023/Journal_Track

• Robust Distortion-free Watermarks for Language Models

  Rohith Kuditipudi, John Thickstun, Tatsunori Hashimoto, Percy Liang, June 2024
  [openreview] [pdf] [bib] [code]

• Enhancing Low-Precision Sampling via Stochastic Gradient Hamiltonian Monte Carlo

  Ziyi Wang, Yujie Chen, Qifan Song, Ruqi Zhang, June 2024
  [openreview] [pdf] [bib] [code]

• Improved Convergence of Score-Based Diffusion Models via Prediction-Correction

  Francesco Pedrotti, Jan Maas, Marco Mondelli, June 2024
  [openreview] [pdf] [bib]

• 'Explaining RL Decisions with Trajectories’: A Reproducibility Study

  Karim Ahmed Abdel Sadek, Matteo Nulli, Joan Velja, Jort Vincenti, May 2024
  [openreview] [pdf] [bib]
  Certifications: Reproducibility Event: reproml.org/MLRC/2023/Journal_Track

• Online Tensor Max-Norm Regularization via Stochastic Optimization

  Tong Wu, May 2024
  [openreview] [pdf] [bib] [code]

• A Study of the Effects of Transfer Learning on Adversarial Robustness

  Pratik Vaishnavi, Kevin Eykholt, Amir Rahmati, May 2024
  [openreview] [pdf] [bib] [code]

• End-to-End Training Induces Information Bottleneck through Layer-Role Differentiation: A Comparative Analysis with Layer-wise Training

  Keitaro Sakamoto, Issei Sato, May 2024
  [openreview] [pdf] [bib]

• Where Did the Gap Go? Reassessing the Long-Range Graph Benchmark

  Jan Tönshoff, Martin Ritzert, Eran Rosenbluth, Martin Grohe, May 2024
  [openreview] [pdf] [bib] [code]

• What Does Softmax Probability Tell Us about Classifiers Ranking Across Diverse Test Conditions?

  Weijie Tu, Weijian Deng, Liang Zheng, Tom Gedeon, May 2024
  [openreview] [pdf] [bib]

• Certified Deductive Reasoning with Language Models

  Gabriel Poesia, Kanishk Gandhi, Eric Zelikman, Noah Goodman, May 2024
  [openreview] [pdf] [bib] [code]

• On the Inherent Privacy Properties of Discrete Denoising Diffusion Models

  Rongzhe Wei, Eleonora Kreacic, Haoyu Peter Wang, Haoteng Yin, Eli Chien, Vamsi K. Potluru, Pan Li, May 2024
  [openreview] [pdf] [bib]

• Online Continual Learning via Logit Adjusted Softmax

  Zhehao Huang, Tao Li, Chenhe Yuan, Yingwen Wu, Xiaolin Huang, May 2024
  [openreview] [pdf] [bib] [code]

• Single Image Test-Time Adaptation for Segmentation

  Klara Janouskova, Tamir Shor, Chaim Baskin, Jiri Matas, May 2024
  [openreview] [pdf] [bib] [code]

• Normed Spaces for Graph Embedding

  Diaaeldin Taha, Wei Zhao, J. Maxwell Riestenberg, Michael Strube, May 2024
  [openreview] [pdf] [bib] [code]

• Uncovering Sets of Maximum Dissimilarity on Random Process Data

  Miguel de Carvalho, Gabriel Martos, May 2024
  [openreview] [pdf] [bib]

• Internal-Coordinate Density Modelling of Protein Structure: Covariance Matters

  Marloes Arts, Jes Frellsen, Wouter Boomsma, May 2024
  [openreview] [pdf] [bib] [code]

• LeanVec: Searching vectors faster by making them fit

  Mariano Tepper, Ishwar Singh Bhati, Cecilia Aguerrebere, Mark Hildebrand, Theodore L. Willke, May 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• CLIP-QDA: An Explainable Concept Bottleneck Model

  Rémi Kazmierczak, Eloïse Berthier, Goran Frehse, Gianni Franchi, May 2024
  [openreview] [pdf] [bib]

• Independence Testing for Temporal Data

  Cencheng Shen, Jaewon Chung, Ronak Mehta, Ting Xu, Joshua T Vogelstein, May 2024
  [openreview] [pdf] [bib] [code]

• Unleashing the Power of Visual Prompting At the Pixel Level

  Junyang Wu, Xianhang Li, Chen Wei, Huiyu Wang, Alan Yuille, Yuyin Zhou, Cihang Xie, May 2024
  [openreview] [pdf] [bib] [code]

• RedMotion: Motion Prediction via Redundancy Reduction

  Royden Wagner, Omer Sahin Tas, Marvin Klemp, Carlos Fernandez, Christoph Stiller, May 2024
  [openreview] [pdf] [bib] [code]

• CLIP meets Model Zoo Experts: Pseudo-Supervision for Visual Enhancement

  Mohammadreza Salehi, Mehrdad Farajtabar, Maxwell Horton, Fartash Faghri, Hadi Pouransari, Raviteja Vemulapalli, Oncel Tuzel, Ali Farhadi, Mohammad Rastegari, Sachin Mehta, May 2024
  [openreview] [pdf] [bib]

• Amortized Bayesian Decision Making for simulation-based models

  Mila Gorecki, Jakob H. Macke, Michael Deistler, May 2024
  [openreview] [pdf] [bib] [code]

• Appropriate Balance of Diversification and Intensification Improves Performance and Efficiency of Adversarial Attacks

  Keiichiro Yamamura, Issa Oe, Nozomi Hata, Hiroki Ishikura, Katsuki Fujisawa, May 2024
  [openreview] [pdf] [bib] [code]

• Reproducibility Study on Adversarial Attacks Against Robust Transformer Trackers

  Fatemeh Nourilenjan Nokabadi, Jean-Francois Lalonde, Christian Gagné, May 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility Event: reproml.org/MLRC/2023/Journal_Track

• Improve Certified Training with Signal-to-Noise Ratio Loss to Decrease Neuron Variance and Increase Neuron Stability

  Tianhao Wei, Ziwei Wang, Peizhi Niu, ABULIKEMU ABUDUWEILI, Weiye Zhao, Casidhe Hutchison, Eric Sample, Changliu Liu, May 2024
  [openreview] [pdf] [bib]

• Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models

  Zhen Lin, Shubhendu Trivedi, Jimeng Sun, May 2024
  [openreview] [pdf] [bib] [code]

• Enhancing Vision-Language Model with Unmasked Token Alignment

  Jihao Liu, Jinliang Zheng, Boxiao Liu, Yu Liu, Hongsheng Li, May 2024
  [openreview] [pdf] [bib]

• Soft Merging of Experts with Adaptive Routing

  Mohammed Muqeeth, Haokun Liu, Colin Raffel, May 2024
  [openreview] [pdf] [bib]
  Certifications: Featured

• MaskOCR: Scene Text Recognition with Masked Vision-Language Pre-training

  Pengyuan Lyu, Chengquan Zhang, Shanshan Liu, Meina Qiao, Yangliu Xu, Liang Wu, Kun Yao, Junyu Han, Errui Ding, Jingdong Wang, May 2024
  [openreview] [pdf] [bib]

• Differentially Private Kernel Inducing Points using features from ScatterNets (DP-KIP-ScatterNet) for Privacy Preserving Data Distillation

  Margarita Vinaroz, Mijung Park, May 2024
  [openreview] [pdf] [bib]

• Large Language Models can be Guided to Evade AI-generated Text Detection

  Ning Lu, Shengcai Liu, Rui He, Yew-Soon Ong, Qi Wang, Ke Tang, May 2024
  [openreview] [pdf] [bib] [code]

• Predicting the Encoding Error of SIRENs

  Jeremy Vonderfecht, Feng Liu, May 2024
  [openreview] [pdf] [bib] [code]

• Adversarial Imitation Learning from Visual Observations using Latent Information

  Vittorio Giammarino, James Queeney, Ioannis Paschalidis, May 2024
  [openreview] [pdf] [bib] [code]

• Transfer Learning with Informative Priors: Simple Baselines Better than Previously Reported

  Ethan Harvey, Mikhail Petrov, Michael C Hughes, May 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility Event: reproml.org/MLRC/2023/Journal_Track

• From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling

  Aneesh Komanduri, Xintao Wu, Yongkai Wu, Feng Chen, May 2024
  [openreview] [pdf] [bib]

• Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning

  Aritra Mitra, George J. Pappas, Hamed Hassani, May 2024
  [openreview] [pdf] [bib]
  Certifications: Event: rl-conference.cc/RLC/2024/Journal_Track

• Genetic InfoMax: Exploring Mutual Information Maximization in High-Dimensional Imaging Genetics Studies

  Yaochen Xie, Ziqian Xie, Sheikh Muhammad Saiful Islam, Degui Zhi, Shuiwang Ji, May 2024
  [openreview] [pdf] [bib]

• Enhancing Compositional Generalization via Compositional Feature Alignment

  Haoxiang Wang, Haozhe Si, Huajie Shao, Han Zhao, May 2024
  [openreview] [pdf] [bib] [code]

• Statistical and Computational Complexities of BFGS Quasi-Newton Method for Generalized Linear Models

  Qiujiang Jin, Tongzheng Ren, Nhat Ho, Aryan Mokhtari, May 2024
  [openreview] [pdf] [bib]

• CascadedGaze: Efficiency in Global Context Extraction for Image Restoration

  Amirhosein Ghasemabadi, Muhammad Kamran Janjua, Mohammad Salameh, CHUNHUA ZHOU, Fengyu Sun, Di Niu, May 2024
  [openreview] [pdf] [bib] [code]

• Revisiting stochastic submodular maximization with cardinality constraint: A bandit perspective

  Pratik Jawanpuria, Bamdev Mishra, Karthik S. Gurumoorthy, May 2024
  [openreview] [pdf] [bib]

• [Re] Explaining Temporal Graph Models through an Explorer-Navigator Framework

  Miklós Hamar, Matey Krastev, Kristiyan Danielov Hristov, David Beglou, May 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Event: reproml.org/MLRC/2023/Journal_Track

• Efficient Large Language Models: A Survey

  Zhongwei Wan, Xin Wang, Che Liu, Samiul Alam, Yu Zheng, Jiachen Liu, Zhongnan Qu, Shen Yan, Yi Zhu, Quanlu Zhang, Mosharaf Chowdhury, Mi Zhang, May 2024
  [openreview] [pdf] [bib]
  Certifications: Survey

• Deep Generalized Prediction Set Classifier and Its Theoretical Guarantees

  Zhou Wang, Xingye Qiao, May 2024
  [openreview] [pdf] [bib]
  Certifications: Featured

• As large as it gets – Studying Infinitely Large Convolutions via Neural Implicit Frequency Filters

  Julia Grabinski, Janis Keuper, Margret Keuper, May 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• TIGERScore: Towards Building Explainable Metric for All Text Generation Tasks

  Dongfu Jiang, Yishan Li, Ge Zhang, Wenhao Huang, Bill Yuchen Lin, Wenhu Chen, May 2024
  [openreview] [pdf] [bib] [code]

• Reproducibility Study of "Learning Perturbations to Explain Time Series Predictions"

  Jiapeng Fan, Luke Cadigan, Paulius Skaisgiris, Sebastian Uriel Arias, May 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility Event: reproml.org/MLRC/2023/Journal_Track

• Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory

  Karthik Somayaji NS, Yu Wang, Malachi Schram, Jan Drgona, Mahantesh M Halappanavar, Frank Liu, Peng Li, May 2024
  [openreview] [pdf] [bib]

• Interpretable Additive Tabular Transformer Networks

  Anton Frederik Thielmann, Arik Reuter, Thomas Kneib, David Rügamer, Benjamin Säfken, May 2024
  [openreview] [pdf] [bib]

• Geometrical aspects of lattice gauge equivariant convolutional neural networks

  David I. Müller, Jimmy Aronsson, Daniel Schuh, May 2024
  [openreview] [pdf] [bib]

• Boosting Data-Driven Mirror Descent with Randomization, Equivariance, and Acceleration

  Hong Ye Tan, Subhadip Mukherjee, Junqi Tang, Carola-Bibiane Schönlieb, May 2024
  [openreview] [pdf] [bib] [code]

• Causal Discovery from Time Series with Hybrids of Constraint-Based and Noise-Based Algorithms

  Daria Bystrova, Charles K. Assaad, Julyan Arbel, Emilie Devijver, Eric Gaussier, Wilfried Thuiller, May 2024
  [openreview] [pdf] [bib] [code]

• GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data

  Xinwei Zhang, Mingyi Hong, Jie Chen, May 2024
  [openreview] [pdf] [bib]

• Training Graph Neural Networks Subject to a Tight Lipschitz Constraint

  Simona Ioana Juvina, Ana Antonia Neacșu, Jérôme Rony, Jean-Christophe Pesquet, Corneliu Burileanu, Ismail Ben Ayed, May 2024
  [openreview] [pdf] [bib] [code]

• GOPlan: Goal-conditioned Offline Reinforcement Learning by Planning with Learned Models

  Mianchu Wang, Rui Yang, Xi Chen, Hao Sun, Meng Fang, Giovanni Montana, May 2024
  [openreview] [pdf] [bib]

• A Short Survey on Importance Weighting for Machine Learning

  Masanari Kimura, Hideitsu Hino, May 2024
  [openreview] [pdf] [bib]
  Certifications: Survey

• Depth Scaling in Graph Neural Networks: Understanding the Flat Curve Behavior

  Diana Gomes, Kyriakos Efthymiadis, Ann Nowe, Peter Vrancx, May 2024
  [openreview] [pdf] [bib] [code]

• Understanding Smoothness of Vector Gaussian Processes on Product Spaces

  Emilio Porcu, Ana Paula Peron, Eugenio Massa, Xavier Emery, May 2024
  [openreview] [pdf] [bib]

• MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Neural Networks

  Charles Arnal, Felix Hensel, Mathieu Carrière, Théo Lacombe, Hiroaki Kurihara, Yuichi Ike, Frederic Chazal, May 2024
  [openreview] [pdf] [bib]

• Regret Bounds for Noise-Free Cascaded Kernelized Bandits

  Zihan Li, Jonathan Scarlett, May 2024
  [openreview] [pdf] [bib]

• The Interplay of Uncertainty Modeling and Deep Active Learning: An Empirical Analysis in Image Classification

  Denis Huseljic, Marek Herde, Yannick Nagel, Lukas Rauch, Paulius Strimaitis, Bernhard Sick, May 2024
  [openreview] [pdf] [bib]

• InduCE: Inductive Counterfactual Explanations for Graph Neural Networks

  Samidha Verma, Burouj Armgaan, Sourav Medya, Sayan Ranu, May 2024
  [openreview] [pdf] [bib]

• G4SATBench: Benchmarking and Advancing SAT Solving with Graph Neural Networks

  Zhaoyu Li, Jinpei Guo, Xujie Si, May 2024
  [openreview] [pdf] [bib] [code]

• Efficient Parallelized Simulation of Cyber-Physical Systems

  Bas van der Heijden, Laura Ferranti, Jens Kober, Robert Babuska, May 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility

• PaDPaF: Partial Disentanglement with Partially-Federated GANs

  Abdulla Jasem Almansoori, Samuel Horváth, Martin Takáč, May 2024
  [openreview] [pdf] [bib] [code]

• Archetypal Analysis++: Rethinking the Initialization Strategy

  Sebastian Mair, Jens Sjölund, May 2024
  [openreview] [pdf] [bib] [code]

• [Re] On the Reproducibility of Post-Hoc Concept Bottleneck Models

  Nesta Midavaine, Gregory Hok Tjoan Go, Diego Canez, Ioana Simion, Satchit Chatterji, May 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Event: reproml.org/MLRC/2023/Journal_Track

• Data Pruning Can Do More: A Comprehensive Data Pruning Approach for Object Re-identification

  Zi Yang, Haojin Yang, Soumajit Majumder, Jorge Cardoso, Guillermo Gallego, May 2024
  [openreview] [pdf] [bib] [code]

• Scaling Vision-and-Language Navigation With Offline RL

  Valay Bundele, Mahesh Bhupati, Biplab Banerjee, Aditya Grover, May 2024
  [openreview] [pdf] [bib] [code]

• Momentum-Based Policy Gradient with Second-Order Information

  Saber Salehkaleybar, Mohammadsadegh Khorasani, Negar Kiyavash, Niao He, Patrick Thiran, May 2024
  [openreview] [pdf] [bib]

• Offline Reinforcement Learning via Tsallis Regularization

  Lingwei Zhu, Matthew Kyle Schlegel, Han Wang, Martha White, May 2024
  [openreview] [pdf] [bib] [code]

• A Survey on Transferability of Adversarial Examples Across Deep Neural Networks

  Jindong Gu, Xiaojun Jia, Pau de Jorge, Wenqian Yu, Xinwei Liu, Avery Ma, Yuan Xun, Anjun Hu, Ashkan Khakzar, Zhijiang Li, Xiaochun Cao, Philip Torr, May 2024
  [openreview] [pdf] [bib] [code]

• Solving Inverse Problems with Model Mismatch using Untrained Neural Networks within Model-based Architectures

  Peimeng Guan, Naveed Iqbal, Mark A. Davenport, Mudassir Masood, May 2024
  [openreview] [pdf] [bib] [code]

• Hybrid Federated Learning for Feature & Sample Heterogeneity: Algorithms and Implementation

  Xinwei Zhang, Wotao Yin, Mingyi Hong, Tianyi Chen, May 2024
  [openreview] [pdf] [bib]

• Fixed Budget Best Arm Identification in Unimodal Bandits

  Debamita Ghosh, Manjesh Kumar Hanawal, Nikola Zlatanov, May 2024
  [openreview] [pdf] [bib] [code]

• Restricted Random Pruning at Initialization for High Compression Range

  Hikari Otsuka, Yasuyuki Okoshi, Ángel López García-Arias, Kazushi Kawamura, Thiem Van Chu, Daichi Fujiki, Masato Motomura, May 2024
  [openreview] [pdf] [bib] [code]

• Continual HyperTransformer: A Meta-Learner for Continual Few-Shot Learning

  Max Vladymyrov, Andrey Zhmoginov, Mark Sandler, May 2024
  [openreview] [pdf] [bib]

• Federated Learning with Convex Global and Local Constraints

  Chuan He, Le Peng, Ju Sun, May 2024
  [openreview] [pdf] [bib] [code]

• Group Fairness in Reinforcement Learning via Multi-Objective Rewards

  Jack Blandin, Ian A. Kash, May 2024
  [openreview] [pdf] [bib] [code]

• On Good Practices for Task-Specific Distillation of Large Pretrained Visual Models

  Juliette Marrie, Michael Arbel, Julien Mairal, Diane Larlus, May 2024
  [openreview] [pdf] [bib]

• Dynamic Online Ensembles of Basis Expansions

  Daniel Waxman, Petar Djuric, May 2024
  [openreview] [pdf] [bib] [code]

• IMEX-Reg: Implicit-Explicit Regularization in the Function Space for Continual Learning

  Prashant Shivaram Bhat, Bharath Chennamkulam Renjith, Elahe Arani, Bahram Zonooz, May 2024
  [openreview] [pdf] [bib] [code]

• Improving Subgraph-GNNs via Edge-Level Ego-Network Encodings

  Nurudin Alvarez-Gonzalez, Andreas Kaltenbrunner, Vicenç Gómez, May 2024
  [openreview] [pdf] [bib] [code]

• DP-ImgSyn: Dataset Alignment for Obfuscated, Differentially Private Image Synthesis

  Efstathia Soufleri, Deepak Ravikumar, Kaushik Roy, May 2024
  [openreview] [pdf] [bib] [code]

• Towards Truly Zero-shot Compositional Visual Reasoning with LLMs as Programmers

  Aleksandar Stanić, Sergi Caelles, Michael Tschannen, May 2024
  [openreview] [pdf] [bib]

• From Stability to Chaos: Analyzing Gradient Descent Dynamics in Quadratic Regression

  Xuxing Chen, Krishna Balasubramanian, Promit Ghosal, Bhavya Kumar Agrawalla, April 2024
  [openreview] [pdf] [bib]

• Using Skew to Assess the Quality of GAN-generated Image Features

  Lorenzo Luzi, Helen Jenne, Carlos Ortiz Marrero, Ryan Murray, April 2024
  [openreview] [pdf] [bib]

• Reproducibility Study of "Explaining RL Decisions with Trajectories"

  Clio Feng, Colin Bot, Bart den Boef, Bart Aaldering, April 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Event: reproml.org/MLRC/2023/Journal_Track

• Identify Ambiguous Tasks Combining Crowdsourced Labels by Weighting Areas Under the Margin

  Tanguy Lefort, Benjamin Charlier, Alexis Joly, Joseph Salmon, April 2024
  [openreview] [pdf] [bib] [code]

• DSI2I: Dense Style for Unpaired Exemplar-based Image-to- Image Translation

  Baran Ozaydin, Tong Zhang, Sabine Susstrunk, Mathieu Salzmann, April 2024
  [openreview] [pdf] [bib] [code]

• A Survey of Temporal Credit Assignment in Deep Reinforcement Learning

  Eduardo Pignatelli, Johan Ferret, Matthieu Geist, Thomas Mesnard, Hado van Hasselt, Laura Toni, April 2024
  [openreview] [pdf] [bib]
  Certifications: Survey

• Improving Diffusion Models for Scene Text Editing with Dual Encoders

  Jiabao Ji, Guanhua Zhang, Zhaowen Wang, Bairu Hou, Zhifei Zhang, Brian L. Price, Shiyu Chang, April 2024
  [openreview] [pdf] [bib] [code]

• Continuous U-Net: Faster, Greater and Noiseless

  Chun-Wun Cheng, Christina Runkel, Lihao Liu, Raymond H. Chan, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero, April 2024
  [openreview] [pdf] [bib]

• Decentralized Decoupled Training for Federated Long-Tailed Learning

  Wenkai Yang, Deli Chen, Hao Zhou, Fandong Meng, Jie Zhou, Xu Sun, April 2024
  [openreview] [pdf] [bib] [code]

• FedConv: Enhancing Convolutional Neural Networks for Handling Data Heterogeneity in Federated Learning

  Peiran Xu, Zeyu Wang, Jieru Mei, Liangqiong Qu, Alan Yuille, Cihang Xie, Yuyin Zhou, April 2024
  [openreview] [pdf] [bib] [code]

• Understanding Sparse Neural Networks from their Topology via Multipartite Graph Representations

  Elia Cunegatti, Matteo Farina, Doina Bucur, Giovanni Iacca, April 2024
  [openreview] [pdf] [bib] [code]

• Differential Equation Scaling Limits of Shaped and Unshaped Neural Networks

  Mufan Bill Li, Mihai Nica, April 2024
  [openreview] [pdf] [bib]
  Certifications: Written by Expert Reviewer

• Stochastic Direct Search Methods for Blind Resource Allocation

  Juliette Achddou, Olivier Cappé, Aurélien Garivier, April 2024
  [openreview] [pdf] [bib] [code]

• Routers in Vision Mixture of Experts: An Empirical Study

  Tianlin Liu, Mathieu Blondel, Carlos Riquelme Ruiz, Joan Puigcerver, April 2024
  [openreview] [pdf] [bib]

• Sketch and shift: a robust decoder for compressive clustering

  Ayoub Belhadji, Rémi Gribonval, April 2024
  [openreview] [pdf] [bib]

• Inference from Real-World Sparse Measurements

  Arnaud Pannatier, Kyle Matoba, François Fleuret, April 2024
  [openreview] [pdf] [bib] [code]

• What Has Been Overlooked in Contrastive Source-Free Domain Adaptation: Leveraging Source-Informed Latent Augmentation within Neighborhood Context

  Jing Wang, Wonho Bae, Jiahong Chen, Kuangen Zhang, Leonid Sigal, Clarence W. de Silva, April 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• E-Valuating Classifier Two-Sample Tests

  Teodora Pandeva, Tim Bakker, Christian A. Naesseth, Patrick Forré, April 2024
  [openreview] [pdf] [bib]

• Semantic Positive Pairs for Enhancing Visual Representation Learning of Instance Discrimination methods

  Mohammad Alkhalefi, Georgios Leontidis, Mingjun Zhong, April 2024
  [openreview] [pdf] [bib]

• What do larger image classifiers memorise?

  Michal Lukasik, Vaishnavh Nagarajan, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar, April 2024
  [openreview] [pdf] [bib]

• Integrated Variational Fourier Features for Fast Spatial Modelling with Gaussian Processes

  Talay M Cheema, Carl Edward Rasmussen, April 2024
  [openreview] [pdf] [bib] [code]

• Time Series Continuous Modeling for Imputation and Forecasting with Implicit Neural Representations

  Etienne Le Naour, Louis Serrano, Léon Migus, Yuan Yin, Ghislain Agoua, Nicolas Baskiotis, patrick gallinari, Vincent Guigue, April 2024
  [openreview] [pdf] [bib] [code]

• Synthesizing Libraries of Programs with Auxiliary Functions

  Habibur Rahman, Thirupathi Reddy Emireddy, Kenneth Tjhia, Elham Parhizkar, Levi Lelis, April 2024
  [openreview] [pdf] [bib] [code]

• Choosing Wisely and Learning Deeply: Selective Cross-Modality Distillation via CLIP for Domain Generalization

  Jixuan Leng, Yijiang Li, Haohan Wang, April 2024
  [openreview] [pdf] [bib] [code]

• Anticipatory Music Transformer

  John Thickstun, David Leo Wright Hall, Chris Donahue, Percy Liang, April 2024
  [openreview] [pdf] [bib] [code]

• Fooling Contrastive Language-Image Pre-Trained Models with CLIPMasterPrints

  Matthias Freiberger, Peter Kun, Christian Igel, Anders Sundnes Løvlie, Sebastian Risi, April 2024
  [openreview] [pdf] [bib] [code]

• A True-to-the-model Axiomatic Benchmark for Graph-based Explainers

  Corrado Monti, Paolo Bajardi, Francesco Bonchi, André Panisson, Alan Perotti, April 2024
  [openreview] [pdf] [bib] [code]

• Variance-aware decision making with linear function approximation under heavy-tailed rewards

  Xiang Li, Qiang Sun, April 2024
  [openreview] [pdf] [bib]

• Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models

  Avi Singh, John D Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Xavier Garcia, Peter J Liu, James Harrison, Jaehoon Lee, Kelvin Xu, Aaron T Parisi, Abhishek Kumar, Alexander A Alemi, Alex Rizkowsky, Azade Nova, Ben Adlam, Bernd Bohnet, Gamaleldin Fathy Elsayed, Hanie Sedghi, Igor Mordatch, Isabelle Simpson, Izzeddin Gur, Jasper Snoek, Jeffrey Pennington, Jiri Hron, Kathleen Kenealy, Kevin Swersky, Kshiteej Mahajan, Laura A Culp, Lechao Xiao, Maxwell Bileschi, Noah Constant, Roman Novak, Rosanne Liu, Tris Warkentin, Yamini Bansal, Ethan Dyer, Behnam Neyshabur, Jascha Sohl-Dickstein, Noah Fiedel, April 2024
  [openreview] [pdf] [bib]
  Certifications: Written by Expert Reviewer

• ZigZag: Universal Sampling-free Uncertainty Estimation Through Two-Step Inference

  Nikita Durasov, Nik Dorndorf, Hieu Le, Pascal Fua, April 2024
  [openreview] [pdf] [bib] [code]

• On the Optimization and Generalization of Multi-head Attention

  Puneesh Deora, Rouzbeh Ghaderi, Hossein Taheri, Christos Thrampoulidis, April 2024
  [openreview] [pdf] [bib]

• Personalised Federated Learning On Heterogeneous Feature Spaces

  Alain Rakotomamonjy, Maxime Vono, Hamlet Jesse Medina Ruiz, Liva Ralaivola, April 2024
  [openreview] [pdf] [bib] [code]

• MUBen: Benchmarking the Uncertainty of Molecular Representation Models

  Yinghao Li, Lingkai Kong, Yuanqi Du, Yue Yu, Yuchen Zhuang, Wenhao Mu, Chao Zhang, April 2024
  [openreview] [pdf] [bib] [code]

• GSURE-Based Diffusion Model Training with Corrupted Data

  Bahjat Kawar, Noam Elata, Tomer Michaeli, Michael Elad, April 2024
  [openreview] [pdf] [bib] [code]

• A note on regularised NTK dynamics with an application to PAC-Bayesian training

  Eugenio Clerico, Benjamin Guedj, April 2024
  [openreview] [pdf] [bib]

• Reproducibility Study of "Robust Fair Clustering: A Novel Fairness Attack and Defense Framework"

  Iason Skylitsis, Zheng Feng, Idries Nasim, Camille Niessink, April 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility Event: reproml.org/MLRC/2023/Journal_Track

• New Evaluation Metrics Capture Quality Degradation due to LLM Watermarking

  Karanpartap Singh, James Zou, April 2024
  [openreview] [pdf] [bib] [code]

• Does Representation Similarity Capture Function Similarity?

  Lucas Hayne, Heejung Jung, R. Carter, April 2024
  [openreview] [pdf] [bib] [code]

• Continual Diffusion: Continual Customization of Text-to-Image Diffusion with C-LoRA

  James Seale Smith, Yen-Chang Hsu, Lingyu Zhang, Ting Hua, Zsolt Kira, Yilin Shen, Hongxia Jin, April 2024
  [openreview] [pdf] [bib]

• BP($\mathbf{\lambda}$): Online Learning via Synthetic Gradients

  Joseph Oliver Pemberton, Rui Ponte Costa, April 2024
  [openreview] [pdf] [bib] [code]

• GUARD: A Safe Reinforcement Learning Benchmark

  Weiye Zhao, Yifan Sun, Feihan Li, Rui Chen, Ruixuan Liu, Tianhao Wei, Changliu Liu, April 2024
  [openreview] [pdf] [bib] [code]

• Incremental Extractive Opinion Summarization Using Cover Trees

  Somnath Basu Roy Chowdhury, Nicholas Monath, Kumar Avinava Dubey, Manzil Zaheer, Andrew McCallum, Amr Ahmed, Snigdha Chaturvedi, April 2024
  [openreview] [pdf] [bib] [code]

• Persistent Local Homology in Graph Learning

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  [openreview] [pdf] [bib] [code]

• Adversarially Robust Spiking Neural Networks Through Conversion

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  [openreview] [pdf] [bib] [code]

• Continual Learning: Applications and the Road Forward

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  [openreview] [pdf] [bib]
  Certifications: Event: lifelong-ml.cc/CoLLAs/2024/Journal_Track

• Anomaly detection with semi-supervised classification based on risk estimators

  Le Thi Khanh Hien, Sukanya Patra, Souhaib Ben Taieb, April 2024
  [openreview] [pdf] [bib] [code]

• Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits

  Daniel Morales-Brotons, Thijs Vogels, Hadrien Hendrikx, April 2024
  [openreview] [pdf] [bib]

• Scalable Hierarchical Self-Attention with Learnable Hierarchy for Long-Range Interactions

  Thuan Nguyen Anh Trang, Khang Nhat Ngo, Hugo Sonnery, Thieu Vo, Siamak Ravanbakhsh, Truong Son Hy, April 2024
  [openreview] [pdf] [bib] [code]

• A Unified View of Differentially Private Deep Generative Modeling

  Dingfan Chen, Raouf Kerkouche, Mario Fritz, April 2024
  [openreview] [pdf] [bib]
  Certifications: Survey

• The Cross-entropy of Piecewise Linear Probability Density Functions

  Tom S. F. Haines, April 2024
  [openreview] [pdf] [bib] [code]

• 3D Molecular Generation via Virtual Dynamics

  Shuqi Lu, Lin Yao, Xi Chen, Hang Zheng, Di He, Guolin Ke, April 2024
  [openreview] [pdf] [bib]

• How good is Good-Turing for Markov samples?

  Prafulla Chandra, Andrew Thangaraj, Nived Rajaraman, April 2024
  [openreview] [pdf] [bib]

• State-wise Constrained Policy Optimization

  Weiye Zhao, Rui Chen, Yifan Sun, Feihan Li, Tianhao Wei, Changliu Liu, April 2024
  [openreview] [pdf] [bib] [code]

• Provable Membership Inference Privacy

  Zachary Izzo, Jinsung Yoon, Sercan O Arik, James Zou, April 2024
  [openreview] [pdf] [bib]

• Adaptive Conformal Regression with Split-Jackknife+ Scores

  Nicolas Deutschmann, Mattia Rigotti, Maria Rodriguez Martinez, April 2024
  [openreview] [pdf] [bib]

• Neural networks can be FLOP-efficient integrators of 1D oscillatory integrands

  Anshuman Sinha, Spencer H Bryngelson, April 2024
  [openreview] [pdf] [bib] [code]

• Towards generalizing deep-audio fake detection networks

  Konstantin Gasenzer, Moritz Wolter, April 2024
  [openreview] [pdf] [bib] [code]

• Scaling (Down) CLIP: A Comprehensive Analysis of Data,Architecture, and Training Strategies

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  [openreview] [pdf] [bib]

• Low-Rank Tensor-Network Encodings for Video-to-Action Behavioral Cloning

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  [openreview] [pdf] [bib]

• EHRDiff : Exploring Realistic EHR Synthesis with Diffusion Models

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  [openreview] [pdf] [bib] [code]

• Understanding Fairness Surrogate Functions in Algorithmic Fairness

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  [openreview] [pdf] [bib]

• Finite-Time Analysis of Entropy-Regularized Neural Natural Actor-Critic Algorithm

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  [openreview] [pdf] [bib]

• PopulAtion Parameter Averaging (PAPA)

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  [openreview] [pdf] [bib] [code]

• The Missing U for Efficient Diffusion Models

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  [openreview] [pdf] [bib] [code]

• CoDeC: Communication-Efficient Decentralized Continual Learning

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  [openreview] [pdf] [bib] [code]

• Bias Amplification Enhances Minority Group Performance

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  [openreview] [pdf] [bib] [code]

• Fast and Expressive Gesture Recognition using a Combination-Homomorphic Electromyogram Encoder

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  [openreview] [pdf] [bib] [code]

• Optimization with Access to Auxiliary Information

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  [openreview] [pdf] [bib] [code]

• Navigating Noise: A Study of How Noise Influences Generalisation and Calibration of Neural Networks

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  [openreview] [pdf] [bib] [code]

• On the Robustness of Neural Collapse and the Neural Collapse of Robustness

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  [openreview] [pdf] [bib] [code]

• Discrete Graph Auto-Encoder

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  [openreview] [pdf] [bib] [code]

• Indexed Minimum Empirical Divergence-Based Algorithms for Linear Bandits

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  [openreview] [pdf] [bib]

• PID Control-Based Self-Healing to Improve the Robustness of Large Language Models

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  [openreview] [pdf] [bib] [code]

• Synthetic data shuffling accelerates the convergence of federated learning under data heterogeneity

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  [openreview] [pdf] [bib] [code]

• Graph Neural Networks Formed via Layer-wise Ensembles of Heterogeneous Base Models

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  [openreview] [pdf] [bib]

• Online Continuous Hyperparameter Optimization for Generalized Linear Contextual Bandits

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  [openreview] [pdf] [bib]

• Faster Convergence of Local SGD for Over-Parameterized Models

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  [openreview] [pdf] [bib]

• Asynchronous Training Schemes in Distributed Learning with Time Delay

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  [openreview] [pdf] [bib]

• Merging by Matching Models in Task Parameter Subspaces

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  [openreview] [pdf] [bib] [code]

• INSPIRE: Incorporating Diverse Feature Preferences in Recourse

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  [openreview] [pdf] [bib] [code]

• Unsupervised 3D Scene Representation Learning via Movable Object Inference

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  [openreview] [pdf] [bib] [code]

• Convergence Analysis of Fractional Gradient Descent

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  [openreview] [pdf] [bib]

• VidEdit: Zero-Shot and Spatially Aware Text-Driven Video Editing

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  [openreview] [pdf] [bib]

• An optimal control perspective on diffusion-based generative modeling

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  [openreview] [pdf] [bib] [code]

• HQ-VAE: Hierarchical Discrete Representation Learning with Variational Bayes

  Yuhta Takida, Yukara Ikemiya, Takashi Shibuya, Kazuki Shimada, Woosung Choi, Chieh-Hsin Lai, Naoki Murata, Toshimitsu Uesaka, Kengo Uchida, Wei-Hsiang Liao, Yuki Mitsufuji, March 2024
  [openreview] [pdf] [bib]

• InfoNCE is variational inference in a recognition parameterised model

  Laurence Aitchison, Stoil Krasimirov Ganev, March 2024
  [openreview] [pdf] [bib]

• Optimal Transport Perturbations for Safe Reinforcement Learning with Robustness Guarantees

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  [openreview] [pdf] [bib] [code]

• New Guarantees for Learning Revenue Maximizing Menus of Lotteries and Two-Part Tariffs

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  [openreview] [pdf] [bib]

• Optical Transformers

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  [openreview] [pdf] [bib]

• Embracing Unknown Step by Step: Towards Reliable Sparse Training in Real World

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  [openreview] [pdf] [bib] [code]

• Revisiting Random Weight Perturbation for Efficiently Improving Generalization

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  [openreview] [pdf] [bib] [code]

• Double Descent and Overfitting under Noisy Inputs and Distribution Shift for Linear Denoisers

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  [openreview] [pdf] [bib] [code]

• From Differential Privacy to Bounds on Membership Inference: Less can be More

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  [openreview] [pdf] [bib]

• CiPR: An Efficient Framework with Cross-instance Positive Relations for Generalized Category Discovery

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  [openreview] [pdf] [bib] [code]

• Introducing "Forecast Utterance" for Conversational Data Science

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  [openreview] [pdf] [bib] [code]

• Voyager: An Open-Ended Embodied Agent with Large Language Models

  Guanzhi Wang, Yuqi Xie, Yunfan Jiang, Ajay Mandlekar, Chaowei Xiao, Yuke Zhu, Linxi Fan, Anima Anandkumar, March 2024
  [openreview] [pdf] [bib] [code]

• Optimal Inference in Contextual Stochastic Block Models

  O Duranthon, Lenka Zdeborova, March 2024
  [openreview] [pdf] [bib] [code]

• Grokking Beyond Neural Networks: An Empirical Exploration with Model Complexity

  Jack William Miller, Charles O'Neill, Thang D Bui, March 2024
  [openreview] [pdf] [bib] [code]

• Compressing the Activation Maps in Deep Convolutional Neural Networks and Its Regularizing Effect

  Minh Hoang Vu, Anders Garpebring, Tufve Nyholm, Tommy Löfstedt, March 2024
  [openreview] [pdf] [bib] [code]

• Towards Understanding Dual BN In Hybrid Adversarial Training

  Chenshuang Zhang, Chaoning Zhang, Kang Zhang, Axi Niu, Junmo Kim, In So Kweon, March 2024
  [openreview] [pdf] [bib]

• ChatGPT Asks, BLIP-2 Answers: Automatic Questioning Towards Enriched Visual Descriptions

  Deyao Zhu, Jun Chen, Kilichbek Haydarov, Xiaoqian Shen, Wenxuan Zhang, Mohamed Elhoseiny, March 2024
  [openreview] [pdf] [bib] [code]

• Revisiting Generalized p-Laplacian Regularized Framelet GCNs: Convergence, Energy Dynamic and as Non-Linear Diffusion

  Dai Shi, Zhiqi Shao, Yi Guo, Qibin Zhao, Junbin Gao, March 2024
  [openreview] [pdf] [bib]

• Inverse Kernel Decomposition

  Chengrui Li, Anqi Wu, March 2024
  [openreview] [pdf] [bib]

• On the Convergence of Adaptive Gradient Methods for Nonconvex Optimization

  Dongruo Zhou, Jinghui Chen, Yuan Cao, Ziyan Yang, Quanquan Gu, March 2024
  [openreview] [pdf] [bib]
  Certifications: Featured

• Granger Causal Interaction Skill Chains

  Caleb Chuck, Kevin Black, Aditya Arjun, Yuke Zhu, Scott Niekum, March 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Event: rl-conference.cc/RLC/2024/Journal_Track

• Predictive Pipelined Decoding: A Compute-Latency Trade-off for Exact LLM Decoding

  Seongjun Yang, Gibbeum Lee, Jaewoong Cho, Dimitris Papailiopoulos, Kangwook Lee, March 2024
  [openreview] [pdf] [bib]

• Maximizing Global Model Appeal in Federated Learning

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  [openreview] [pdf] [bib] [code]

• Learning Sparse Graphs for Functional Regression using Graph-induced Operator-valued Kernels

  Akash Saha, Balamurugan Palaniappan, March 2024
  [openreview] [pdf] [bib] [code]

• Addressing Attribute Bias with Adversarial Support-Matching

  Thomas Kehrenberg, Myles Bartlett, Viktoriia Sharmanska, Novi Quadrianto, March 2024
  [openreview] [pdf] [bib] [code]

• Hyper-parameter Tuning for Fair Classification without Sensitive Attribute Access

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  [openreview] [pdf] [bib]

• E(n)-equivariant Graph Neural Cellular Automata

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  [openreview] [pdf] [bib] [code]

• Layer-diverse Negative Sampling for Graph Neural Networks

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  [openreview] [pdf] [bib]

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  [openreview] [pdf] [bib]

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  [openreview] [pdf] [bib]
  Certifications: Written by Expert Reviewer

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  [openreview] [pdf] [bib] [code]

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  [openreview] [pdf] [bib] [code]

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  [openreview] [pdf] [bib] [code]

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  [openreview] [pdf] [bib] [code]

• How does over-squashing affect the power of GNNs?

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  [openreview] [pdf] [bib]

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  [openreview] [pdf] [bib]
  Certifications: Event: automl.cc/AutoML/2024/Journal_Track

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  [openreview] [pdf] [bib]

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  [openreview] [pdf] [bib]

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  [openreview] [pdf] [bib] [code]

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  [openreview] [pdf] [bib] [code]

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  [openreview] [pdf] [bib] [code]
  Certifications: Featured

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  [openreview] [pdf] [bib] [code]

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  [openreview] [pdf] [bib] [code]

• Demographically-Informed Prediction Discrepancy Index: Early Warnings of Demographic Biases for Unlabeled Populations

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  [openreview] [pdf] [bib] [code]

• Fast Training of Diffusion Models with Masked Transformers

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  [openreview] [pdf] [bib] [code]

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  [openreview] [pdf] [bib]

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  [openreview] [pdf] [bib] [code]

• Incorporating Prior Knowledge into Neural Networks through an Implicit Composite Kernel

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  [openreview] [pdf] [bib] [code]

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  [openreview] [pdf] [bib]

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  [openreview] [pdf] [bib]

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  [openreview] [pdf] [bib] [code]

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  [openreview] [pdf] [bib] [code]

• Kernel Normalized Convolutional Networks

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  [openreview] [pdf] [bib] [code]

• A VAE-based Framework for Learning Multi-Level Neural Granger-Causal Connectivity

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  [openreview] [pdf] [bib] [code]

• Exploit CAM by itself: Complementary Learning System for Weakly Supervised Semantic Segmentation

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  [openreview] [pdf] [bib] [code]

• Learning from Natural Language Feedback

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  [openreview] [pdf] [bib] [code]

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  [openreview] [pdf] [bib] [code]

• Pseudo-Differential Neural Operator: Generalize Fourier Neural operator for Learning Solution Operators of Partial Differential Equations

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  [openreview] [pdf] [bib]

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  [openreview] [pdf] [bib] [code]

• Multitask Learning Can Improve Worst-Group Outcomes

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  [openreview] [pdf] [bib] [code]

• ASPEST: Bridging the Gap Between Active Learning and Selective Prediction

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  [openreview] [pdf] [bib] [code]

• Statistical Component Separation for Targeted Signal Recovery in Noisy Mixtures

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  [openreview] [pdf] [bib] [code]

• A density estimation perspective on learning from pairwise human preferences

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  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

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  [openreview] [pdf] [bib] [code]

• ModuLoRA: Finetuning 2-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

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  [openreview] [pdf] [bib]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• Leveraging Endo- and Exo-Temporal Regularization for Black-box Video Domain Adaptation

  Yuecong Xu, Jianfei Yang, Haozhi Cao, Min Wu, Xiaoli Li, Lihua Xie, Zhenghua Chen, February 2024
  [openreview] [pdf] [bib] [code]

• Correlation Clustering with Active Learning of Pairwise Similarities

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  [openreview] [pdf] [bib] [code]

• Effective Latent Differential Equation Models via Attention and Multiple Shooting

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  [openreview] [pdf] [bib] [code]

• Global Convergence of SGD For Logistic Loss on Two Layer Neural Nets

  Pulkit Gopalani, Samyak Jha, Anirbit Mukherjee, February 2024
  [openreview] [pdf] [bib]

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  [openreview] [pdf] [bib]

• Enhancing Robustness to Class-Conditional Distribution Shift in Long-Tailed Recognition

  Keliang Li, Hong Chang, Shiguang Shan, Xilin CHEN, February 2024
  [openreview] [pdf] [bib]

• InPars-Light: Cost-Effective Unsupervised Training of Efficient Rankers

  Leonid Boytsov, Preksha Patel, Vivek Sourabh, Riddhi Nisar, Sayani Kundu, Ramya Ramanathan, Eric Nyberg, February 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility

• Cognitive Architectures for Language Agents

  Theodore Sumers, Shunyu Yao, Karthik Narasimhan, Thomas Griffiths, February 2024
  [openreview] [pdf] [bib]
  Certifications: Survey

• From Continuous Dynamics to Graph Neural Networks: Neural Diffusion and Beyond

  Andi Han, Dai Shi, Lequan Lin, Junbin Gao, February 2024
  [openreview] [pdf] [bib]
  Certifications: Survey

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  Taman Narayan, Serena Lutong Wang, Kevin Robert Canini, Maya Gupta, February 2024
  [openreview] [pdf] [bib] [code]

• The Slingshot Effect: A Late-Stage Optimization Anomaly in Adaptive Gradient Methods

  Vimal Thilak, Etai Littwin, Shuangfei Zhai, Omid Saremi, Roni Paiss, Joshua M. Susskind, February 2024
  [openreview] [pdf] [bib]

• Mixed Nash for Robust Federated Learning

  Wanyun Xie, Thomas Pethick, Ali Ramezani-Kebrya, Volkan Cevher, February 2024
  [openreview] [pdf] [bib]

• Policy Gradient with Kernel Quadrature

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  [openreview] [pdf] [bib]

• PNeRV: A Polynomial Neural Representation for Videos

  Sonam Gupta, Snehal Singh Tomar, Grigorios Chrysos, Sukhendu Das, Rajagopalan N Ambasamduram, February 2024
  [openreview] [pdf] [bib]

• Automated Design of Metaheuristic Algorithms: A Survey

  Qi Zhao, Qiqi Duan, Bai Yan, Shi Cheng, Yuhui Shi, February 2024
  [openreview] [pdf] [bib]
  Certifications: Survey

• Exploring Simple, High Quality Out-of-Distribution Detection with L2 Normalization

  Jarrod Haas, William Yolland, Bernhard T Rabus, February 2024
  [openreview] [pdf] [bib]

• On the Out-of-Distribution Coverage of Combining Split Conformal Prediction and Bayesian Deep Learning

  Paul Scemama, Ariel Kapusta, February 2024
  [openreview] [pdf] [bib]

• Estimating Optimal Policy Value in Linear Contextual Bandits Beyond Gaussianity

  Jonathan Lee, Weihao Kong, Aldo Pacchiano, Vidya Muthukumar, Emma Brunskill, February 2024
  [openreview] [pdf] [bib] [code]

• DynaConF: Dynamic Forecasting of Non-Stationary Time Series

  Siqi Liu, Andreas Lehrmann, February 2024
  [openreview] [pdf] [bib] [code]

• QDC: Quantum Diffusion Convolution Kernels on Graphs

  Thomas Markovich, February 2024
  [openreview] [pdf] [bib]

• Image Reconstruction via Deep Image Prior Subspaces

  Riccardo Barbano, Javier Antoran, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin, Zeljko Kereta, February 2024
  [openreview] [pdf] [bib]

• On the Dual Problem of Convexified Convolutional Neural Networks

  Site Bai, Chuyang Ke, Jean Honorio, February 2024
  [openreview] [pdf] [bib]

• Accountable Textual-Visual Chat Learns to Reject Human Instructions in Image Re-creation

  Zhiwei Zhang, Yuliang Liu, February 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Survey

• Evaluating Spatial Understanding of Large Language Models

  Yutaro Yamada, Yihan Bao, Andrew Kyle Lampinen, Jungo Kasai, Ilker Yildirim, February 2024
  [openreview] [pdf] [bib] [code]

• Robust Learning Rate Selection for Stochastic Optimization via Splitting Diagnostic

  Matteo Sordello, Niccolo Dalmasso, Hangfeng He, Weijie J Su, February 2024
  [openreview] [pdf] [bib]

• Transfer Learning for High-dimensional Quantile Regression with Statistical Guarantee

  Sheng Qiao, Yong He, Wenxin Zhou, February 2024
  [openreview] [pdf] [bib]

• Recovering Exact Support in Federated lasso without Optimization

  Adarsh Barik, Jean Honorio, February 2024
  [openreview] [pdf] [bib]

• Distributional GFlowNets with Quantile Flows

  Dinghuai Zhang, Ling Pan, Ricky T. Q. Chen, Aaron Courville, Yoshua Bengio, February 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Models of human preference for learning reward functions

  W. Bradley Knox, Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter Stone, Alessandro G Allievi, February 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Event: rl-conference.cc/RLC/2024/Journal_Track

• NorMatch: Matching Normalizing Flows with Discriminative Classifiers for Semi-Supervised Learning

  Zhongying Deng, Rihuan Ke, Carola-Bibiane Schönlieb, Angelica I Aviles-Rivero, February 2024
  [openreview] [pdf] [bib] [code]

• Mitigating Off-Policy Bias in Actor-Critic Methods with One-Step Q-learning: A Novel Correction Approach

  Baturay Saglam, Doğan Can Çiçek, Furkan Burak Mutlu, Suleyman Kozat, February 2024
  [openreview] [pdf] [bib] [code]

• Provable Guarantees for Sparsity Recovery with Deterministic Missing Data Patterns

  Chuyang Ke, Jean Honorio, February 2024
  [openreview] [pdf] [bib]

• Visual Prompt Based Personalized Federated Learning

  Guanghao Li, Wansen Wu, Yan Sun, Li Shen, Baoyuan Wu, Dacheng Tao, February 2024
  [openreview] [pdf] [bib] [code]

• CR-MoE: Consistent Routed Mixture-of-Experts for Scaling Contrastive Learning

  Ziyu Jiang, Guoqing Zheng, Yu Cheng, Ahmed Hassan Awadallah, Zhangyang Wang, February 2024
  [openreview] [pdf] [bib] [code]

• Leveraging Function Space Aggregation for Federated Learning at Scale

  Nikita Dhawan, Nicole Elyse Mitchell, Zachary Charles, Zachary Garrett, Gintare Karolina Dziugaite, February 2024
  [openreview] [pdf] [bib]
  Certifications: Written by Expert Reviewer

• Error Bounds for Flow Matching Methods

  Joe Benton, George Deligiannidis, Arnaud Doucet, February 2024
  [openreview] [pdf] [bib]

• Non-Uniform Smoothness for Gradient Descent

  Albert S. Berahas, Lindon Roberts, Fred Roosta, February 2024
  [openreview] [pdf] [bib]

• Hierarchical Neural Simulation-Based Inference Over Event Ensembles

  Lukas Heinrich, Siddharth Mishra-Sharma, Chris Pollard, Philipp Windischhofer, February 2024
  [openreview] [pdf] [bib] [code]

• What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?

  Songyang Han, Sanbao Su, Sihong He, Shuo Han, Haizhao Yang, Shaofeng Zou, Fei Miao, February 2024
  [openreview] [pdf] [bib] [code]

• MESSY Estimation: Maximum-Entropy based Stochastic and Symbolic densitY Estimation

  Tony Tohme, Mohsen Sadr, KAMAL YOUCEF-TOUMI, Nicolas Hadjiconstantinou, February 2024
  [openreview] [pdf] [bib]

• Controlling Federated Learning for Covertness

  Adit Jain, Vikram Krishnamurthy, February 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Event: automl.cc/AutoML/2024/Journal_Track

• The Fair Value of Data Under Heterogeneous Privacy Constraints in Federated Learning

  Justin Singh Kang, Ramtin Pedarsani, Kannan Ramchandran, February 2024
  [openreview] [pdf] [bib]

• Out-of-Distribution Optimality of Invariant Risk Minimization

  Shoji Toyota, Kenji Fukumizu, February 2024
  [openreview] [pdf] [bib]

• When is Momentum Extragradient Optimal? A Polynomial-Based Analysis

  Junhyung Lyle Kim, Gauthier Gidel, Anastasios Kyrillidis, Fabian Pedregosa, February 2024
  [openreview] [pdf] [bib]

• DDLP: Unsupervised Object-centric Video Prediction with Deep Dynamic Latent Particles

  Tal Daniel, Aviv Tamar, February 2024
  [openreview] [pdf] [bib] [code]

• A Unified View on Solving Objective Mismatch in Model-Based Reinforcement Learning

  Ran Wei, Nathan Lambert, Anthony D McDonald, Alfredo Garcia, Roberto Calandra, February 2024
  [openreview] [pdf] [bib]
  Certifications: Survey

• Introspective Experience Replay: Look Back When Surprised

  Ramnath Kumar, Dheeraj Mysore Nagaraj, February 2024
  [openreview] [pdf] [bib] [code]

• Domain-Generalizable Multiple-Domain Clustering

  Amit Rozner, Barak Battash, Lior Wolf, Ofir Lindenbaum, February 2024
  [openreview] [pdf] [bib] [code]

• RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation

  Konstantinos Bousmalis, Giulia Vezzani, Dushyant Rao, Coline Manon Devin, Alex X. Lee, Maria Bauza Villalonga, Todor Davchev, Yuxiang Zhou, Agrim Gupta, Akhil Raju, Antoine Laurens, Claudio Fantacci, Valentin Dalibard, Martina Zambelli, Murilo Fernandes Martins, Rugile Pevceviciute, Michiel Blokzijl, Misha Denil, Nathan Batchelor, Thomas Lampe, Emilio Parisotto, Konrad Zolna, Scott Reed, Sergio Gómez Colmenarejo, Jonathan Scholz, Abbas Abdolmaleki, Oliver Groth, Jean-Baptiste Regli, Oleg Sushkov, Thomas Rothörl, Jose Enrique Chen, Yusuf Aytar, David Barker, Joy Ortiz, Martin Riedmiller, Jost Tobias Springenberg, Raia Hadsell, Francesco Nori, Nicolas Heess, February 2024
  [openreview] [pdf] [bib]

• Fixed-Budget Best-Arm Identification in Sparse Linear Bandits

  Recep Can Yavas, Vincent Y. F. Tan, February 2024
  [openreview] [pdf] [bib] [code]

• Understanding the Role of Layer Normalization in Label-Skewed Federated Learning

  Guojun Zhang, Mahdi Beitollahi, Alex Bie, Xi Chen, February 2024
  [openreview] [pdf] [bib] [code]

• Learning to Abstain From Uninformative Data

  Yikai Zhang, Songzhu Zheng, Mina Dalirrooyfard, Pengxiang Wu, Anderson Schneider, Anant Raj, Yuriy Nevmyvaka, Chao Chen, February 2024
  [openreview] [pdf] [bib] [code]

• WaveBench: Benchmarking Data-driven Solvers for Linear Wave Propagation PDEs

  Tianlin Liu, Jose Antonio Lara Benitez, Florian Faucher, AmirEhsan Khorashadizadeh, Maarten V. de Hoop, Ivan Dokmanić, February 2024
  [openreview] [pdf] [bib] [code]

• Using Motion Cues to Supervise Single-frame Body Pose & Shape Estimation in Low Data Regimes

  Andrey Davydov, Alexey Sidnev, Artsiom Sanakoyeu, Yuhua Chen, Mathieu Salzmann, Pascal Fua, February 2024
  [openreview] [pdf] [bib] [code]

• LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations

  Yudong Xu, Wenhao Li, Pashootan Vaezipoor, Scott Sanner, Elias Boutros Khalil, February 2024
  [openreview] [pdf] [bib] [code]

• Candidate Set Re-ranking for Composed Image Retrieval with Dual Multi-modal Encoder

  Zheyuan Liu, Weixuan Sun, Damien Teney, Stephen Gould, February 2024
  [openreview] [pdf] [bib] [code]

• A Review of the Applications of Deep Learning-Based Emergent Communication

  Brendon Boldt, David R Mortensen, February 2024
  [openreview] [pdf] [bib]

• Data-Dependent Generalization Bounds for Neural Networks with ReLU

  Harsh Pandey, Amitabha Bagchi, Srikanta J. Bedathur, Arindam Bhattacharya, February 2024
  [openreview] [pdf] [bib]

• Two Failures of Self-Consistency in the Multi-Step Reasoning of LLMs

  Angelica Chen, Jason Phang, Alicia Parrish, Vishakh Padmakumar, Chen Zhao, Samuel R. Bowman, Kyunghyun Cho, February 2024
  [openreview] [pdf] [bib]

• MOCA: Self-supervised Representation Learning by Predicting Masked Online Codebook Assignments

  Spyros Gidaris, Andrei Bursuc, Oriane Siméoni, Antonín Vobecký, Nikos Komodakis, Matthieu Cord, Patrick Perez, February 2024
  [openreview] [pdf] [bib] [code]

• Transfer Learning for Bayesian Optimization on Heterogeneous Search Spaces

  Zhou Fan, Xinran Han, Zi Wang, February 2024
  [openreview] [pdf] [bib] [code]

• A Multilinear Least-Squares Formulation for Sparse Tensor Canonical Correlation Analysis

  Jun Yu, Zhaoming Kong, Kun Chen, Xin Zhang, Yong Chen, Lifang He, February 2024
  [openreview] [pdf] [bib] [code]

• Generalizing Neural Additive Models via Statistical Multimodal Analysis

  Young Kyung Kim, Juan Matias Di Martino, Guillermo Sapiro, February 2024
  [openreview] [pdf] [bib] [code]

• A Joint Study of Phrase Grounding and Task Performance in Vision and Language Models

  Noriyuki Kojima, Hadar Averbuch-Elor, Yoav Artzi, February 2024
  [openreview] [pdf] [bib]

• Size Lowerbounds for Deep Operator Networks

  Anirbit Mukherjee, Amartya Roy, February 2024
  [openreview] [pdf] [bib]

• Extending Path-Dependent NJ-ODEs to Noisy Observations and a Dependent Observation Framework

  William Andersson, Jakob Heiss, Florian Krach, Josef Teichmann, January 2024
  [openreview] [pdf] [bib] [code]

• Blind Biological Sequence Denoising with Self-Supervised Set Learning

  Nathan Hoyen Ng, Ji Won Park, Jae Hyeon Lee, Ryan Lewis Kelly, Stephen Ra, Kyunghyun Cho, January 2024
  [openreview] [pdf] [bib]

• We're Not Using Videos Effectively: An Updated Domain Adaptive Video Segmentation Baseline

  Simar Kareer, Vivek Vijaykumar, Harsh Maheshwari, Judy Hoffman, Prithvijit Chattopadhyay, Viraj Uday Prabhu, January 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility

• Unsupervised Discovery of Steerable Factors When Graph Deep Generative Models Are Entangled

  Shengchao Liu, Chengpeng Wang, Jiarui Lu, Weili Nie, Hanchen Wang, Zhuoxinran Li, Bolei Zhou, Jian Tang, January 2024
  [openreview] [pdf] [bib] [code]

• Are you using test log-likelihood correctly?

  Sameer Deshpande, Soumya Ghosh, Tin D. Nguyen, Tamara Broderick, January 2024
  [openreview] [pdf] [bib]

• Blockwise Self-Supervised Learning at Scale

  Shoaib Siddiqui, David Krueger, Yann LeCun, Stephane Deny, January 2024
  [openreview] [pdf] [bib] [code]

• Temporally Rich Deep Learning Models for Magnetoencephalography

  Tim Chard, Mark Dras, Paul Sowman, Steve Cassidy, Jia Wu, January 2024
  [openreview] [pdf] [bib] [code]

• Disciplined Saddle Programming

  Philipp Schiele, Eric Sager Luxenberg, Stephen P. Boyd, January 2024
  [openreview] [pdf] [bib] [code]

• Federated Sampling with Langevin Algorithm under Isoperimetry

  Lukang Sun, Adil Salim, Peter Richtárik, January 2024
  [openreview] [pdf] [bib]

• TensorVAE: a simple and efficient generative model for conditional molecular conformation generation

  Hongyang Yu, Hongjiang Yu, January 2024
  [openreview] [pdf] [bib] [code]

• PixMIM: Rethinking Pixel Reconstruction in Masked Image Modeling

  Yuan Liu, Songyang Zhang, Jiacheng Chen, Kai Chen, Dahua Lin, January 2024
  [openreview] [pdf] [bib] [code]

• Break it, Imitate it, Fix it: Robustness by Generating Human-Like Attacks

  Aradhana Sinha, Ananth Balashankar, Ahmad Beirami, Thi Avrahami, Jilin Chen, Alex Beutel, January 2024
  [openreview] [pdf] [bib]
  Certifications: Written by Expert Reviewer

• MMD-Regularized Unbalanced Optimal Transport

  Piyushi Manupriya, SakethaNath Jagarlapudi, Pratik Jawanpuria, January 2024
  [openreview] [pdf] [bib] [code]

• Bandits Corrupted by Nature: Lower Bounds on Regret and Robust Optimistic Algorithms

  Timothée Mathieu, Debabrota Basu, Odalric-Ambrym Maillard, January 2024
  [openreview] [pdf] [bib]

• High-dimensional Bayesian Optimization via Covariance Matrix Adaptation Strategy

  Lam Ngo, Huong Ha, Jeffrey Chan, Vu Nguyen, Hongyu Zhang, January 2024
  [openreview] [pdf] [bib] [code]

• A general framework for formulating structured variable selection

  GUANBO WANG, Mireille Schnitzer, Tom Chen, Rui Wang, Robert W Platt, January 2024
  [openreview] [pdf] [bib]

• Towards fully covariant machine learning

  Soledad Villar, David W Hogg, Weichi Yao, George A Kevrekidis, Bernhard Schölkopf, January 2024
  [openreview] [pdf] [bib] [code]

• Empowering GNNs via Edge-Aware Weisfeiler-Leman Algorithm

  Meng Liu, Haiyang Yu, Shuiwang Ji, January 2024
  [openreview] [pdf] [bib]

• A Survey on Graph Construction for Geometric Deep Learning in Medicine: Methods and Recommendations

  Tamara T. Müller, Sophie Starck, Alina Dima, Stephan Wunderlich, Kyriaki-Margarita Bintsi, Kamilia Zaripova, Rickmer Braren, Daniel Rueckert, Anees Kazi, Georgios Kaissis, January 2024
  [openreview] [pdf] [bib]
  Certifications: Survey

• To Transfer or Not to Transfer: Suppressing Concepts from Source Representations

  Vijay Sadashivaiah, Keerthiram Murugesan, Ronny Luss, Pin-Yu Chen, Chris Sims, James Hendler, Amit Dhurandhar, January 2024
  [openreview] [pdf] [bib]

• On the Choice of Learning Rate for Local SGD

  Lukas Balles, Prabhu Teja S, Cedric Archambeau, January 2024
  [openreview] [pdf] [bib]

• Semantic similarity prediction is better than other semantic similarity measures

  Steffen Herbold, January 2024
  [openreview] [pdf] [bib] [code]

• Prismer: A Vision-Language Model with Multi-Task Experts

  Shikun Liu, Linxi Fan, Edward Johns, Zhiding Yu, Chaowei Xiao, Anima Anandkumar, January 2024
  [openreview] [pdf] [bib] [code]

• CAREER: A Foundation Model for Labor Sequence Data

  Keyon Vafa, Emil Palikot, Tianyu Du, Ayush Kanodia, Susan Athey, David Blei, January 2024
  [openreview] [pdf] [bib] [code]

• Hyperspherical Prototype Node Clustering

  Jitao Lu, Danyang Wu, Feiping Nie, Rong Wang, Xuelong Li, January 2024
  [openreview] [pdf] [bib] [code]

• AdaFed: Fair Federated Learning via Adaptive Common Descent Direction

  Shayan Mohajer Hamidi, EN-HUI YANG, January 2024
  [openreview] [pdf] [bib]

• Wavelet Networks: Scale-Translation Equivariant Learning From Raw Time-Series

  David W. Romero, Erik J Bekkers, Jakub M. Tomczak, Mark Hoogendoorn, January 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Variational autoencoder with weighted samples for high-dimensional non-parametric adaptive importance sampling

  Julien Demange-Chryst, Francois Bachoc, Jérôme Morio, Timothé Krauth, January 2024
  [openreview] [pdf] [bib] [code]

• Separability Analysis for Causal Discovery in Mixture of DAGs

  Burak Varici, Dmitriy Katz, Dennis Wei, Prasanna Sattigeri, Ali Tajer, January 2024
  [openreview] [pdf] [bib] [code]

• Unleashing the Potential of Acquisition Functions in High-Dimensional Bayesian Optimization

  Jiayu Zhao, Renyu Yang, SHENGHAO QIU, Zheng Wang, January 2024
  [openreview] [pdf] [bib] [code]

• On the Adversarial Robustness of Camera-based 3D Object Detection

  Shaoyuan Xie, Zichao Li, Zeyu Wang, Cihang Xie, January 2024
  [openreview] [pdf] [bib] [code]

• AmbientFlow: Invertible generative models from incomplete, noisy measurements

  Varun A. Kelkar, Rucha Deshpande, Arindam Banerjee, Mark Anastasio, January 2024
  [openreview] [pdf] [bib] [code]

• Multi-Horizon Representations with Hierarchical Forward Models for Reinforcement Learning

  Trevor McInroe, Lukas Schäfer, Stefano V Albrecht, January 2024
  [openreview] [pdf] [bib]

• Neural Task Synthesis for Visual Programming

  Victor-Alexandru Pădurean, Georgios Tzannetos, Adish Singla, January 2024
  [openreview] [pdf] [bib] [code]

• Federated Classification in Hyperbolic Spaces via Secure Aggregation of Convex Hulls

  Saurav Prakash, Jin Sima, Chao Pan, Eli Chien, Olgica Milenkovic, January 2024
  [openreview] [pdf] [bib] [code]

• Personalized Algorithmic Recourse with Preference Elicitation

  Giovanni De Toni, Paolo Viappiani, Stefano Teso, Bruno Lepri, Andrea Passerini, January 2024
  [openreview] [pdf] [bib] [code]

• Wasserstein Distributionally Robust Policy Evaluation and Learning for Contextual Bandits

  Yi Shen, Pan Xu, Michael Zavlanos, January 2024
  [openreview] [pdf] [bib]
  Certifications: Featured

• A Fully Decentralized Surrogate for Multi-Agent Policy Optimization

  Kefan Su, Zongqing Lu, January 2024
  [openreview] [pdf] [bib] [code]

• A Globally Convergent Algorithm for Neural Network Parameter Optimization Based on Difference-of-Convex Functions

  Daniel Tschernutter, Mathias Kraus, Stefan Feuerriegel, January 2024
  [openreview] [pdf] [bib]

• Online Reference Tracking For Linear Systems with Unknown Dynamics and Unknown Disturbances

  Nariman Niknejad, Farnaz Adib Yaghmaie, Hamidreza Modares, January 2024
  [openreview] [pdf] [bib]

• DINOv2: Learning Robust Visual Features without Supervision

  Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy V. Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel HAZIZA, Francisco Massa, Alaaeldin El-Nouby, Mido Assran, Nicolas Ballas, Wojciech Galuba, Russell Howes, Po-Yao Huang, Shang-Wen Li, Ishan Misra, Michael Rabbat, Vasu Sharma, Gabriel Synnaeve, Hu Xu, Herve Jegou, Julien Mairal, Patrick Labatut, Armand Joulin, Piotr Bojanowski, January 2024
  [openreview] [pdf] [bib] [code]

• Boomerang: Local sampling on image manifolds using diffusion models

  Lorenzo Luzi, Paul M Mayer, Josue Casco-Rodriguez, Ali Siahkoohi, Richard Baraniuk, January 2024
  [openreview] [pdf] [bib]

• Improved Regret Bounds for Linear Adversarial MDPs via Linear Optimization

  Fang Kong, XiangCheng Zhang, Baoxiang Wang, Shuai Li, January 2024
  [openreview] [pdf] [bib]

• Neural Circuit Diagrams: Robust Diagrams for the Communication, Implementation, and Analysis of Deep Learning Architectures

  Vincent Abbott, January 2024
  [openreview] [pdf] [bib] [code]

• DyG2Vec: Efficient Representation Learning for Dynamic Graphs

  Mohammad Alomrani, Mahdi Biparva, Yingxue Zhang, Mark Coates, January 2024
  [openreview] [pdf] [bib] [code]

• A Survey on Out-of-Distribution Detection in NLP

  Hao Lang, Yinhe Zheng, Yixuan Li, Jian SUN, Fei Huang, Yongbin Li, January 2024
  [openreview] [pdf] [bib]

• Proximal Mean Field Learning in Shallow Neural Networks

  Alexis Teter, Iman Nodozi, Abhishek Halder, January 2024
  [openreview] [pdf] [bib] [code]

• Synaptic Interaction Penalty: Appropriate Penalty Term for Energy-Efficient Spiking Neural Networks

  Kazuma Suetake, Takuya Ushimaru, Ryuji Saiin, Yoshihide Sawada, January 2024
  [openreview] [pdf] [bib]

• Neural Implicit Manifold Learning for Topology-Aware Density Estimation

  Brendan Leigh Ross, Gabriel Loaiza-Ganem, Anthony L. Caterini, Jesse C. Cresswell, January 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Exploring Format Consistency for Instruction Tuning

  Shihao Liang, Runchu Tian, Kunlun Zhu, Yujia Qin, Huadong Wang, Xin Cong, Zhiyuan Liu, Xiaojiang Liu, Maosong Sun, January 2024
  [openreview] [pdf] [bib] [code]

• Variational Classification: A Probabilistic Generalization of the Softmax Classifier

  Shehzaad Zuzar Dhuliawala, Mrinmaya Sachan, Carl Allen, January 2024
  [openreview] [pdf] [bib]

• Pathologies of Predictive Diversity in Deep Ensembles

  Taiga Abe, E. Kelly Buchanan, Geoff Pleiss, John Patrick Cunningham, January 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• DIG In: Evaluating Disparities in Image Generations with Indicators for Geographic Diversity

  Melissa Hall, Candace Ross, Adina Williams, Nicolas Carion, Michal Drozdzal, Adriana Romero-Soriano, January 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback

  Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony Tong Wang, Samuel Marks, Charbel-Raphael Segerie, Micah Carroll, Andi Peng, Phillip Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, Eric J Michaud, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Biyik, Anca Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell, December 2023
  [openreview] [pdf] [bib]
  Certifications: Survey

• A Survey on the Possibilities & Impossibilities of AI-generated Text Detection

  Soumya Suvra Ghosal, Souradip Chakraborty, Jonas Geiping, Furong Huang, Dinesh Manocha, Amrit Bedi, December 2023
  [openreview] [pdf] [bib]
  Certifications: Survey

• FREED++: Improving RL Agents for Fragment-Based Molecule Generation by Thorough Reproduction

  Alexander Telepov, Artem Tsypin, Kuzma Khrabrov, Sergey Yakukhnov, Pavel Strashnov, Petr Zhilyaev, Egor Rumiantsev, Daniel Ezhov, Manvel Avetisian, Olga Popova, Artur Kadurin, December 2023
  [openreview] [pdf] [bib] [code]

• In search of projectively equivariant networks

  Georg Bökman, Axel Flinth, Fredrik Kahl, December 2023
  [openreview] [pdf] [bib] [code]

• Improving Native CNN Robustness with Filter Frequency Regularization

  Jovita Lukasik, Paul Gavrikov, Janis Keuper, Margret Keuper, December 2023
  [openreview] [pdf] [bib] [code]

• Resmax: An Alternative Soft-Greedy Operator for Reinforcement Learning

  Erfan Miahi, Revan MacQueen, Alex Ayoub, Abbas Masoumzadeh, Martha White, December 2023
  [openreview] [pdf] [bib] [code]

• Privacy Budget Tailoring in Private Data Analysis

  Daniel Alabi, Chris Wiggins, December 2023
  [openreview] [pdf] [bib]

• Modular Deep Learning

  Jonas Pfeiffer, Sebastian Ruder, Ivan Vulić, Edoardo Ponti, December 2023
  [openreview] [pdf] [bib]
  Certifications: Survey

• Smoothed Differential Privacy

  Ao Liu, Yu-Xiang Wang, Lirong Xia, December 2023
  [openreview] [pdf] [bib] [code]

• Distributed Architecture Search Over Heterogeneous Distributions

  Erum Mushtaq, Chaoyang He, Jie Ding, Salman Avestimehr, December 2023
  [openreview] [pdf] [bib] [code]

• DreamEdit: Subject-driven Image Editing

  Tianle Li, Max Ku, Cong Wei, Wenhu Chen, December 2023
  [openreview] [pdf] [bib] [code]

• UnIVAL: Unified Model for Image, Video, Audio and Language Tasks

  Mustafa Shukor, Corentin Dancette, Alexandre Rame, Matthieu Cord, December 2023
  [openreview] [pdf] [bib] [code]

• IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages

  Jay Gala, Pranjal A Chitale, A K Raghavan, Varun Gumma, Sumanth Doddapaneni, Aswanth Kumar M, Janki Atul Nawale, Anupama Sujatha, Ratish Puduppully, Vivek Raghavan, Pratyush Kumar, Mitesh M Khapra, Raj Dabre, Anoop Kunchukuttan, December 2023
  [openreview] [pdf] [bib] [code]

• Towards Optimization-Friendly Binary Neural Network

  Nianhui Guo, Joseph Bethge, Hong Guo, Christoph Meinel, Haojin Yang, December 2023
  [openreview] [pdf] [bib] [code]

• Equivariant MuZero

  Andreea Deac, Theophane Weber, George Papamakarios, December 2023
  [openreview] [pdf] [bib]

• On the Efficacy of Differentially Private Few-shot Image Classification

  Marlon Tobaben, Aliaksandra Shysheya, John F Bronskill, Andrew Paverd, Shruti Tople, Santiago Zanella-Beguelin, Richard E Turner, Antti Honkela, December 2023
  [openreview] [pdf] [bib] [code]

• Benchmarks for Physical Reasoning AI

  Andrew Melnik, Robin Schiewer, Moritz Lange, Andrei Ioan Muresanu, mozhgan saeidi, Animesh Garg, Helge Ritter, December 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Survey

• StarCoder: may the source be with you!

  Raymond Li, Loubna Ben allal, Yangtian Zi, Niklas Muennighoff, Denis Kocetkov, Chenghao Mou, Marc Marone, Christopher Akiki, Jia LI, Jenny Chim, Qian Liu, Evgenii Zheltonozhskii, Terry Yue Zhuo, Thomas Wang, Olivier Dehaene, Joel Lamy-Poirier, Joao Monteiro, Nicolas Gontier, Ming-Ho Yee, Logesh Kumar Umapathi, Jian Zhu, Ben Lipkin, Muhtasham Oblokulov, Zhiruo Wang, Rudra Murthy, Jason T Stillerman, Siva Sankalp Patel, Dmitry Abulkhanov, Marco Zocca, Manan Dey, Zhihan Zhang, Urvashi Bhattacharyya, Wenhao Yu, Sasha Luccioni, Paulo Villegas, Fedor Zhdanov, Tony Lee, Nadav Timor, Jennifer Ding, Claire S Schlesinger, Hailey Schoelkopf, Jan Ebert, Tri Dao, Mayank Mishra, Alex Gu, Carolyn Jane Anderson, Brendan Dolan-Gavitt, Danish Contractor, Siva Reddy, Daniel Fried, Dzmitry Bahdanau, Yacine Jernite, Carlos Muñoz Ferrandis, Sean Hughes, Thomas Wolf, Arjun Guha, Leandro Von Werra, Harm de Vries, December 2023
  [openreview] [pdf] [bib]
  Certifications: Reproducibility

• Mixture of Dynamical Variational Autoencoders for Multi-Source Trajectory Modeling and Separation

  Xiaoyu Lin, Laurent Girin, Xavier Alameda-Pineda, December 2023
  [openreview] [pdf] [bib] [code]

• Fast Slate Policy Optimization: Going Beyond Plackett-Luce

  Otmane Sakhi, David Rohde, Nicolas Chopin, December 2023
  [openreview] [pdf] [bib]

• Error bounds and dynamics of bootstrapping in actor-critic reinforcement learning

  Ahmed J Zerouali, Douglas Blair Tweed, December 2023
  [openreview] [pdf] [bib] [code]

• SHAP-XRT: The Shapley Value Meets Conditional Independence Testing

  Jacopo Teneggi, Beepul Bharti, Yaniv Romano, Jeremias Sulam, December 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Federated Minimax Optimization with Client Heterogeneity

  Pranay Sharma, Rohan Panda, Gauri Joshi, December 2023
  [openreview] [pdf] [bib]

• Towards Fair Video Summarization

  Anshuman Chhabra, Kartik Patwari, Chandana Kuntala, Sristi, Deepak Kumar Sharma, Prasant Mohapatra, December 2023
  [openreview] [pdf] [bib] [code]

• Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior

  Javier Antoran, Riccardo Barbano, Johannes Leuschner, José Miguel Hernández-Lobato, Bangti Jin, December 2023
  [openreview] [pdf] [bib] [code]

• Early Stopping for Deep Image Prior

  Hengkang Wang, Taihui Li, Zhong Zhuang, Tiancong Chen, Hengyue Liang, Ju Sun, December 2023
  [openreview] [pdf] [bib] [code]

• Image retrieval outperforms diffusion models on data augmentation

  Max F Burg, Florian Wenzel, Dominik Zietlow, Max Horn, Osama Makansi, Francesco Locatello, Chris Russell, December 2023
  [openreview] [pdf] [bib]

• Transport with Support: Data-Conditional Diffusion Bridges

  Ella Tamir, Martin Trapp, Arno Solin, December 2023
  [openreview] [pdf] [bib] [code]

• Local Function Complexity for Active Learning via Mixture of Gaussian Processes

  Danny Panknin, Stefan Chmiela, Klaus Robert Muller, Shinichi Nakajima, December 2023
  [openreview] [pdf] [bib] [code]

• Towards a General Transfer Approach for Policy-Value Networks

  Dennis J. N. J. Soemers, Vegard Mella, Eric Piette, Matthew Stephenson, Cameron Browne, Olivier Teytaud, December 2023
  [openreview] [pdf] [bib] [code]

• ProtoCaps: A Fast and Non-Iterative Capsule Network Routing Method

  Miles Everett, Mingjun Zhong, Georgios Leontidis, December 2023
  [openreview] [pdf] [bib] [code]

• Detecting danger in gridworlds using Gromov’s Link Condition

  Thomas F Burns, Robert Tang, December 2023
  [openreview] [pdf] [bib] [code]

• Partial Optimal Transport for Support Subset Selection

  Bilal Riaz, Yuksel Karahan, Austin J. Brockmeier, December 2023
  [openreview] [pdf] [bib]

• Wrapped $\beta$-Gaussians with compact support for exact probabilistic modeling on manifolds

  Sergey Troshin, Vlad Niculae, December 2023
  [openreview] [pdf] [bib] [code]

• GIT-Net: Generalized Integral Transform for Operator Learning

  Chao Wang, Alexandre H. Thiery, December 2023
  [openreview] [pdf] [bib] [code]

• Semi-Supervised Single Domain Generalization with Label-Free Adversarial Data Augmentation

  Ronghang Zhu, Xiang Yu, Sheng Li, December 2023
  [openreview] [pdf] [bib]

• Beyond Boundaries: A Novel Data-Augmentation Discourse for Open Domain Generalization

  Shirsha Bose, Ankit Jha, Hitesh Kandala, Biplab Banerjee, December 2023
  [openreview] [pdf] [bib]

• Accelerating Batch Active Learning Using Continual Learning Techniques

  Arnav Mohanty Das, Gantavya Bhatt, Megh Manoj Bhalerao, Vianne R. Gao, Rui Yang, Jeff Bilmes, December 2023
  [openreview] [pdf] [bib]

• Revisiting Topic-Guided Language Models

  Carolina Zheng, Keyon Vafa, David Blei, December 2023
  [openreview] [pdf] [bib] [code]

• Two-Level Actor-Critic Using Multiple Teachers

  Su Zhang, Srijita Das, Sriram Ganapathi Subramanian, Matthew E. Taylor, December 2023
  [openreview] [pdf] [bib]

• ECG Representation Learning with Multi-Modal EHR Data

  Sravan Kumar Lalam, Hari Krishna Kunderu, Shayan Ghosh, Harish Kumar A, Samir Awasthi, Ashim Prasad, Francisco Lopez-Jimenez, Zachi I Attia, Samuel Asirvatham, Paul Friedman, Rakesh Barve, Melwin Babu, November 2023
  [openreview] [pdf] [bib]

• Variational Causal Dynamics: Discovering Modular World Models from Interventions

  Anson Lei, Bernhard Schölkopf, Ingmar Posner, November 2023
  [openreview] [pdf] [bib]

• Causal Reinforcement Learning: A Survey

  Zhihong Deng, Jing Jiang, Guodong Long, Chengqi Zhang, November 2023
  [openreview] [pdf] [bib]
  Certifications: Survey

• RCT Rejection Sampling for Causal Estimation Evaluation

  Katherine A. Keith, Sergey Feldman, David Jurgens, Jonathan Bragg, Rohit Bhattacharya, November 2023
  [openreview] [pdf] [bib] [code]

• Tight conditions for when the NTK approximation is valid

  Enric Boix-Adserà, Etai Littwin, November 2023
  [openreview] [pdf] [bib]

• Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods

  Avery Ma, Yangchen Pan, Amir-massoud Farahmand, November 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• Data-Free Diversity-Based Ensemble Selection for One-Shot Federated Learning

  Naibo Wang, Wenjie Feng, yuchen deng, Moming Duan, Fusheng Liu, See-Kiong Ng, November 2023
  [openreview] [pdf] [bib] [code]

• Learning to reconstruct signals from binary measurements alone

  Julián Tachella, Laurent Jacques, November 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• Universal Graph Continual Learning

  Thanh Duc Hoang, Do Viet Tung, Duy-Hung Nguyen, Bao-Sinh Nguyen, Huy Hoang Nguyen, Hung Le, November 2023
  [openreview] [pdf] [bib]

• Cross-client Label Propagation for Transductive and Semi-Supervised Federated Learning

  Jonathan Scott, Michelle Yeo, Christoph H Lampert, November 2023
  [openreview] [pdf] [bib] [code]

• MERMAIDE: Learning to Align Learners using Model-Based Meta-Learning

  Arundhati Banerjee, Soham Rajesh Phade, Stefano Ermon, Stephan Zheng, November 2023
  [openreview] [pdf] [bib]

• Meta Continual Learning on Graphs with Experience Replay

  Altay Unal, Abdullah Akgül, Melih Kandemir, Gozde Unal, November 2023
  [openreview] [pdf] [bib] [code]

• Pairwise Learning with Adaptive Online Gradient Descent

  Tao Sun, Qingsong Wang, Yunwen Lei, Dongsheng Li, Bao Wang, November 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Improved identification accuracy in equation learning via comprehensive $\boldsymbol{R^2}$-elimination and Bayesian model selection

  Daniel Nickelsen, Bubacarr Bah, November 2023
  [openreview] [pdf] [bib]

• Reliable Active Learning via Influence Functions

  Meng Xia, Ricardo Henao, November 2023
  [openreview] [pdf] [bib]

• Personalized Federated Learning with Communication Compression

  El houcine Bergou, Konstantin Pavlovich Burlachenko, Aritra Dutta, Peter Richtárik, November 2023
  [openreview] [pdf] [bib]

• Uncovering Unique Concept Vectors through Latent Space Decomposition

  Mara Graziani, Laura O'Mahony, An-phi Nguyen, Henning Müller, Vincent Andrearczyk, November 2023
  [openreview] [pdf] [bib] [code]

• RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment

  Hanze Dong, Wei Xiong, Deepanshu Goyal, Yihan Zhang, Winnie Chow, Rui Pan, Shizhe Diao, Jipeng Zhang, KaShun SHUM, Tong Zhang, November 2023
  [openreview] [pdf] [bib] [code]

• SANTA: Source Anchoring Network and Target Alignment for Continual Test Time Adaptation

  Goirik Chakrabarty, Manogna Sreenivas, Soma Biswas, November 2023
  [openreview] [pdf] [bib] [code]

• The Analysis of the Expected Change in the Classification Probability of the Predicted Label

  Ruo Yang, Ping Liu, Mustafa Bilgic, November 2023
  [openreview] [pdf] [bib]

• Latent State Models of Training Dynamics

  Michael Y. Hu, Angelica Chen, Naomi Saphra, Kyunghyun Cho, November 2023
  [openreview] [pdf] [bib] [code]

• Differentially Private Optimizers Can Learn Adversarially Robust Models

  Zhiqi Bu, Yuan Zhang, November 2023
  [openreview] [pdf] [bib] [code]

• Addressing caveats of neural persistence with deep graph persistence

  Leander Girrbach, Anders Christensen, Ole Winther, Zeynep Akata, A. Sophia Koepke, November 2023
  [openreview] [pdf] [bib] [code]

• Replay-enhanced Continual Reinforcement Learning

  Tiantian Zhang, Kevin Zehua Shen, Zichuan Lin, Bo Yuan, Xueqian Wang, Xiu Li, Deheng Ye, November 2023
  [openreview] [pdf] [bib] [code]

• The (Un)Scalability of Informed Heuristic Function Estimation in NP-Hard Search Problems

  Sumedh Pendurkar, Taoan Huang, Brendan Juba, Jiapeng Zhang, Sven Koenig, Guni Sharon, November 2023
  [openreview] [pdf] [bib] [code]

• Provably Safe Reinforcement Learning: Conceptual Analysis, Survey, and Benchmarking

  Hanna Krasowski, Jakob Thumm, Marlon Müller, Lukas Schäfer, Xiao Wang, Matthias Althoff, November 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Survey

• A Combinatorial Semi-Bandit Approach to Charging Station Selection for Electric Vehicles

  Niklas Åkerblom, Morteza Haghir Chehreghani, November 2023
  [openreview] [pdf] [bib] [code]

• Invertible Hierarchical Generative Model for Images

  Heikki Timonen, Miika Aittala, Jaakko Lehtinen, November 2023
  [openreview] [pdf] [bib] [code]

• PAVI: Plate-Amortized Variational Inference

  Louis Rouillard, Alexandre Le Bris, Thomas Moreau, Demian Wassermann, November 2023
  [openreview] [pdf] [bib]
  Certifications: Reproducibility

• Using Representation Expressiveness and Learnability to Evaluate Self-Supervised Learning Methods

  Yuchen Lu, Zhen Liu, Aristide Baratin, Romain Laroche, Aaron Courville, Alessandro Sordoni, November 2023
  [openreview] [pdf] [bib]

• Learning Multiscale Non-stationary Causal Structures

  Gabriele D'Acunto, Gianmarco De Francisci Morales, Paolo Bajardi, Francesco Bonchi, November 2023
  [openreview] [pdf] [bib]

• Bag of Image Patch Embedding Behind the Success of Self-Supervised Learning

  Yubei Chen, Adrien Bardes, ZENGYI LI, Yann LeCun, November 2023
  [openreview] [pdf] [bib]

• One-Round Active Learning through Data Utility Learning and Proxy Models

  Jiachen T. Wang, Si Chen, Ruoxi Jia, November 2023
  [openreview] [pdf] [bib]

• Bridging the Gap Between Offline and Online Reinforcement Learning Evaluation Methodologies

  Shivakanth Sujit, Pedro Braga, Jorg Bornschein, Samira Ebrahimi Kahou, November 2023
  [openreview] [pdf] [bib] [code]

• RLTF: Reinforcement Learning from Unit Test Feedback

  Jiate Liu, Yiqin Zhu, Kaiwen Xiao, QIANG FU, Xiao Han, Yang Wei, Deheng Ye, November 2023
  [openreview] [pdf] [bib] [code]

• Visualizing the Diversity of Representations Learned by Bayesian Neural Networks

  Dennis Grinwald, Kirill Bykov, Shinichi Nakajima, Marina MC Höhne, November 2023
  [openreview] [pdf] [bib]

• Automated Detection of Causal Inference Opportunities: Regression Discontinuity Subgroup Discovery

  Tony Liu, Patrick Lawlor, Lyle Ungar, Konrad Kording, Rahul Ladhania, November 2023
  [openreview] [pdf] [bib] [code]

• Invariant Structure Learning for Better Generalization and Causal Explainability

  Yunhao Ge, Sercan O Arik, Jinsung Yoon, Ao Xu, Laurent Itti, Tomas Pfister, November 2023
  [openreview] [pdf] [bib] [code]

• Data pruning and neural scaling laws: fundamental limitations of score-based algorithms

  Fadhel Ayed, Soufiane Hayou, November 2023
  [openreview] [pdf] [bib]

• Offline Reinforcement Learning with Additional Covering Distributions

  Chenjie Mao, November 2023
  [openreview] [pdf] [bib]

• Online model selection by learning how compositional kernels evolve

  Eura Shin, Predrag Klasnja, Susan Murphy, Finale Doshi-Velez, November 2023
  [openreview] [pdf] [bib] [code]

• NOFLITE: Learning to Predict Individual Treatment Effect Distributions

  Toon Vanderschueren, Jeroen Berrevoets, Wouter Verbeke, November 2023
  [openreview] [pdf] [bib] [code]

• Stochastic Mirror Descent: Convergence Analysis and Adaptive Variants via the Mirror Stochastic Polyak Stepsize

  Ryan D'Orazio, Nicolas Loizou, Issam H. Laradji, Ioannis Mitliagkas, November 2023
  [openreview] [pdf] [bib] [code]

• Provably Personalized and Robust Federated Learning

  Mariel Werner, Lie He, Michael Jordan, Martin Jaggi, Sai Praneeth Karimireddy, November 2023
  [openreview] [pdf] [bib]

• Conditional Sampling of Variational Autoencoders via Iterated Approximate Ancestral Sampling

  Vaidotas Simkus, Michael U. Gutmann, November 2023
  [openreview] [pdf] [bib] [code]

• Rewiring with Positional Encodings for Graph Neural Networks

  Rickard Brüel Gabrielsson, Mikhail Yurochkin, Justin Solomon, November 2023
  [openreview] [pdf] [bib]

• A Robust Backpropagation-Free Framework for Images

  Timothy Zee, Alex Ororbia, Ankur Mali, Ifeoma Nwogu, November 2023
  [openreview] [pdf] [bib] [code]

• Minorization-Maximization for Learning Determinantal Point Processes

  Takahiro Kawashima, Hideitsu Hino, November 2023
  [openreview] [pdf] [bib] [code]

• Understanding Curriculum Learning in Policy Optimization for Online Combinatorial Optimization

  Runlong Zhou, Zelin He, Yuandong Tian, Yi Wu, Simon Shaolei Du, November 2023
  [openreview] [pdf] [bib] [code]

• Training DNNs Resilient to Adversarial and Random Bit-Flips by Learning Quantization Ranges

  Kamran Chitsaz, Goncalo Mordido, Jean-Pierre David, François Leduc-Primeau, November 2023
  [openreview] [pdf] [bib] [code]

• Feature-Attending Recurrent Modules for Generalization in Reinforcement Learning

  Wilka Torrico Carvalho, Andrew Kyle Lampinen, Kyriacos Nikiforou, Felix Hill, Murray Shanahan, November 2023
  [openreview] [pdf] [bib] [code]

• Achieving Risk Control in Online Learning Settings

  Shai Feldman, Liran Ringel, Stephen Bates, Yaniv Romano, November 2023
  [openreview] [pdf] [bib] [code]

• Exploring Transformer Backbones for Heterogeneous Treatment Effect Estimation

  YiFan Zhang, Hanlin Zhang, Zachary Chase Lipton, Li Erran Li, Eric Xing, November 2023
  [openreview] [pdf] [bib] [code]

• GraphPNAS: Learning Probabilistic Graph Generators for Neural Architecture Search

  Muchen Li, Jeffrey Yunfan Liu, Leonid Sigal, Renjie Liao, November 2023
  [openreview] [pdf] [bib] [code]

• Federated Learning under Partially Disjoint Data via Manifold Reshaping

  Ziqing Fan, Jiangchao Yao, Ruipeng Zhang, Lingjuan Lyu, Yanfeng Wang, Ya Zhang, November 2023
  [openreview] [pdf] [bib] [code]

• Improving Continual Learning by Accurate Gradient Reconstructions of the Past

  Erik Daxberger, Siddharth Swaroop, Kazuki Osawa, Rio Yokota, Richard E Turner, José Miguel Hernández-Lobato, Mohammad Emtiyaz Khan, November 2023
  [openreview] [pdf] [bib]
  Certifications: Event: lifelong-ml.cc/CoLLAs/2024/Journal_Track

• Synthetic Data from Diffusion Models Improves ImageNet Classification

  Shekoofeh Azizi, Simon Kornblith, Chitwan Saharia, Mohammad Norouzi, David J. Fleet, November 2023
  [openreview] [pdf] [bib]

• ILPO-MP: Mode Priors Prevent Mode Collapse when Imitating Latent Policies from Observations

  Oliver Struckmeier, Ville Kyrki, November 2023
  [openreview] [pdf] [bib]

• Complementary Sparsity: Accelerating Sparse CNNs with High Accuracy on General-Purpose Computing Platforms

  Kang Zhao, Yijun Tan, Kai Han, Ting Hu, Hanting Chen, Tao Yuan, Yunhe Wang, Jun Yao, November 2023
  [openreview] [pdf] [bib]

• Finding Neurons in a Haystack: Case Studies with Sparse Probing

  Wes Gurnee, Neel Nanda, Matthew Pauly, Katherine Harvey, Dmitrii Troitskii, Dimitris Bertsimas, November 2023
  [openreview] [pdf] [bib] [code]

• SIESTA: Efficient Online Continual Learning with Sleep

  Md Yousuf Harun, Jhair Gallardo, Tyler L. Hayes, Ronald Kemker, Christopher Kanan, November 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Event: lifelong-ml.cc/CoLLAs/2024/Journal_Track

• Inducing Meaningful Units from Character Sequences with Dynamic Capacity Slot Attention

  Melika Behjati, James Henderson, November 2023
  [openreview] [pdf] [bib]

• Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks

  Wenhu Chen, Xueguang Ma, Xinyi Wang, William W. Cohen, November 2023
  [openreview] [pdf] [bib] [code]

• DP-LFlow: Differentially Private Latent Flow for Scalable Sensitive Image Generation

  Dihong Jiang, Sun Sun, November 2023
  [openreview] [pdf] [bib] [code]

• Binary Classification under Local Label Differential Privacy Using Randomized Response Mechanisms

  Shirong Xu, Chendi Wang, Will Wei Sun, Guang Cheng, November 2023
  [openreview] [pdf] [bib] [code]

• Learn the Time to Learn: Replay Scheduling in Continual Learning

  Marcus Klasson, Hedvig Kjellstrom, Cheng Zhang, November 2023
  [openreview] [pdf] [bib] [code]

• Neighborhood Gradient Mean: An Efficient Decentralized Learning Method for Non-IID Data

  Sai Aparna Aketi, Sangamesh Kodge, Kaushik Roy, October 2023
  [openreview] [pdf] [bib] [code]

• Limitation of Characterizing Implicit Regularization by Data-independent Functions

  Leyang Zhang, Zhi-Qin John Xu, Tao Luo, Yaoyu Zhang, October 2023
  [openreview] [pdf] [bib]

• Population-based Evaluation in Repeated Rock-Paper-Scissors as a Benchmark for Multiagent Reinforcement Learning

  Marc Lanctot, John Schultz, Neil Burch, Max Olan Smith, Daniel Hennes, Thomas Anthony, Julien Perolat, October 2023
  [openreview] [pdf] [bib] [code]

• Convergence of SGD for Training Neural Networks with Sliced Wasserstein Losses

  Eloi Tanguy, October 2023
  [openreview] [pdf] [bib]

• Not All Causal Inference is the Same

  Matej Zečević, Devendra Singh Dhami, Kristian Kersting, October 2023
  [openreview] [pdf] [bib] [code]

• Homomorphic Self-Supervised Learning

  T. Anderson Keller, Xavier Suau, Luca Zappella, October 2023
  [openreview] [pdf] [bib]

• Multimodal Language Learning for Object Retrieval in Low Data Regimes in the Face of Missing Modalities

  Kasra Darvish, Edward Raff, Francis Ferraro, Cynthia Matuszek, October 2023
  [openreview] [pdf] [bib] [code]

• Worst-case Feature Risk Minimization for Data-Efficient Learning

  Jingshi Lei, Da Li, Chengming Xu, Liming Fang, Timothy Hospedales, Yanwei Fu, October 2023
  [openreview] [pdf] [bib]

• Conformal prediction under ambiguous ground truth

  David Stutz, Abhijit Guha Roy, Tatiana Matejovicova, Patricia Strachan, Ali Taylan Cemgil, Arnaud Doucet, October 2023
  [openreview] [pdf] [bib]

• Towards Stability of Autoregressive Neural Operators

  Michael McCabe, Peter Harrington, Shashank Subramanian, Jed Brown, October 2023
  [openreview] [pdf] [bib] [code]

• $f$-MICL: Understanding and Generalizing InfoNCE-based Contrastive Learning

  Yiwei Lu, Guojun Zhang, Sun Sun, Hongyu Guo, Yaoliang Yu, October 2023
  [openreview] [pdf] [bib]

• Non-Stationary Contextual Pricing with Safety Constraints

  Dheeraj Baby, Jianyu Xu, Yu-Xiang Wang, October 2023
  [openreview] [pdf] [bib]

• VoLTA: Vision-Language Transformer with Weakly-Supervised Local-Feature Alignment

  Shraman Pramanick, Li Jing, Sayan Nag, Jiachen Zhu, Hardik J Shah, Yann LeCun, Rama Chellappa, October 2023
  [openreview] [pdf] [bib] [code]

• Benefits of Max Pooling in Neural Networks: Theoretical and Experimental Evidence

  Kyle Matoba, Nikolaos Dimitriadis, François Fleuret, October 2023
  [openreview] [pdf] [bib] [code]

• Local Advantage Networks for Multi-Agent Reinforcement Learning in Dec-POMDPs

  Raphaël Avalos, Mathieu Reymond, Ann Nowe, Diederik M Roijers, October 2023
  [openreview] [pdf] [bib]

• Beyond Distribution Shift: Spurious Features Through the Lens of Training Dynamics

  Nihal Murali, Aahlad Manas Puli, Ke Yu, Rajesh Ranganath, kayhan Batmanghelich, October 2023
  [openreview] [pdf] [bib] [code]

• Pareto Actor-Critic for Equilibrium Selection in Multi-Agent Reinforcement Learning

  Filippos Christianos, Georgios Papoudakis, Stefano V Albrecht, October 2023
  [openreview] [pdf] [bib] [code]

• Bridging Imitation and Online Reinforcement Learning: An Optimistic Tale

  Botao Hao, Rahul Jain, Dengwang Tang, Zheng Wen, October 2023
  [openreview] [pdf] [bib]

• Gradient Masked Averaging for Federated Learning

  Irene Tenison, Sai Aravind Sreeramadas, Vaikkunth Mugunthan, Edouard Oyallon, Irina Rish, Eugene Belilovsky, October 2023
  [openreview] [pdf] [bib]

• Training Vision-Language Transformers from Captions

  Liangke Gui, Yingshan Chang, Qiuyuan Huang, Subhojit Som, Alexander G Hauptmann, Jianfeng Gao, Yonatan Bisk, October 2023
  [openreview] [pdf] [bib] [code]

• Policy Gradient Algorithms Implicitly Optimize by Continuation

  Adrien Bolland, Gilles Louppe, Damien Ernst, October 2023
  [openreview] [pdf] [bib]

• Inverse Scaling: When Bigger Isn't Better

  Ian R. McKenzie, Alexander Lyzhov, Michael Martin Pieler, Alicia Parrish, Aaron Mueller, Ameya Prabhu, Euan McLean, Xudong Shen, Joe Cavanagh, Andrew George Gritsevskiy, Derik Kauffman, Aaron T. Kirtland, Zhengping Zhou, Yuhui Zhang, Sicong Huang, Daniel Wurgaft, Max Weiss, Alexis Ross, Gabriel Recchia, Alisa Liu, Jiacheng Liu, Tom Tseng, Tomasz Korbak, Najoung Kim, Samuel R. Bowman, Ethan Perez, October 2023
  [openreview] [pdf] [bib]
  Certifications: Featured

• Self-Attention in Colors: Another Take on Encoding Graph Structure in Transformers

  Romain Menegaux, Emmanuel Jehanno, Margot Selosse, Julien Mairal, October 2023
  [openreview] [pdf] [bib] [code]

• Identifying latent distances with Finslerian geometry

  Alison Pouplin, David Eklund, Carl Henrik Ek, Søren Hauberg, October 2023
  [openreview] [pdf] [bib] [code]

• Discretization Invariant Networks for Learning Maps between Neural Fields

  Clinton Wang, Polina Golland, October 2023
  [openreview] [pdf] [bib] [code]

• Multi-label Node Classification On Graph-Structured Data

  Tianqi Zhao, Thi Ngan Dong, Alan Hanjalic, Megha Khosla, October 2023
  [openreview] [pdf] [bib]

• Physics informed neural networks for elliptic equations with oscillatory differential operators

  Arnav Gangal, Luis Kim, Sean Patrick Carney, October 2023
  [openreview] [pdf] [bib]

• Greedier is Better: Selecting Multiple Neighbors per Iteration for Sparse Subspace Clustering

  Jwo-Yuh Wu, Liang-Chi Huang, Wen Hsuan Li, Chun-Hung Liu, Rung-Hung Gau, October 2023
  [openreview] [pdf] [bib]

• Distributed Newton-Type Methods with Communication Compression and Bernoulli Aggregation

  Rustem Islamov, Xun Qian, Slavomir Hanzely, Mher Safaryan, Peter Richtárik, October 2023
  [openreview] [pdf] [bib]

• Fourier Features in Reinforcement Learning with Neural Networks

  David Brellmann, David Filliat, Goran Frehse, October 2023
  [openreview] [pdf] [bib] [code]

• Diagnostic Tool for Out-of-Sample Model Evaluation

  Ludvig Hult, Dave Zachariah, Peter Stoica, October 2023
  [openreview] [pdf] [bib] [code]

• Straggler-Resilient Personalized Federated Learning

  Isidoros Tziotis, Zebang Shen, Ramtin Pedarsani, Hamed Hassani, Aryan Mokhtari, October 2023
  [openreview] [pdf] [bib] [code]

• Self-supervised Learning for Segmentation and Quantification of Dopamine Neurons in Parkinson’s Disease

  Fatemeh Haghighi, soumitra ghosh, Sarah Chu, Hai Ngu, Mohsen Hejrati, Han Hui Lin, Baris Bingol, Somaye Hashemifar, October 2023
  [openreview] [pdf] [bib]

• Dual Cognitive Architecture: Incorporating Biases and Multi-Memory Systems for Lifelong Learning

  Shruthi Gowda, Bahram Zonooz, Elahe Arani, October 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Event: lifelong-ml.cc/CoLLAs/2024/Journal_Track

• Analysis of Convolutions, Non-linearity and Depth in Graph Neural Networks using Neural Tangent Kernel

  Mahalakshmi Sabanayagam, Pascal Esser, Debarghya Ghoshdastidar, October 2023
  [openreview] [pdf] [bib] [code]

• Zero-shot Node Classification with Graph Contrastive Embedding Network

  Wei Ju, Yifang Qin, Siyu Yi, Zhengyang Mao, Kangjie Zheng, Luchen Liu, Xiao Luo, Ming Zhang, October 2023
  [openreview] [pdf] [bib]

• Sharper Rates and Flexible Framework for Nonconvex SGD with Client and Data Sampling

  Alexander Tyurin, Lukang Sun, Konstantin Pavlovich Burlachenko, Peter Richtárik, October 2023
  [openreview] [pdf] [bib]

• Private GANs, Revisited

  Alex Bie, Gautam Kamath, Guojun Zhang, October 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Survey

• An Analysis of Model-Based Reinforcement Learning From Abstracted Observations

  Rolf A. N. Starre, Marco Loog, Elena Congeduti, Frans A Oliehoek, October 2023
  [openreview] [pdf] [bib]

• The Kernel Density Integral Transformation

  Calvin McCarter, October 2023
  [openreview] [pdf] [bib] [code]

• Overcoming Resource Constraints in Federated Learning: Large Models Can Be Trained with only Weak Clients

  Yue Niu, Saurav Prakash, Souvik Kundu, Sunwoo Lee, Salman Avestimehr, October 2023
  [openreview] [pdf] [bib] [code]

• Projected Randomized Smoothing for Certified Adversarial Robustness

  Samuel Pfrommer, Brendon G. Anderson, Somayeh Sojoudi, October 2023
  [openreview] [pdf] [bib] [code]

• Multi-Domain Long-Tailed Learning by Augmenting Disentangled Representations

  Xinyu Yang, Huaxiu Yao, Allan Zhou, Chelsea Finn, October 2023
  [openreview] [pdf] [bib]

• Improved baselines for vision-language pre-training

  Enrico Fini, Pietro Astolfi, Adriana Romero-Soriano, Jakob Verbeek, Michal Drozdzal, October 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• CAE v2: Context Autoencoder with CLIP Latent Alignment

  Xinyu Zhang, Jiahui Chen, Junkun Yuan, Qiang Chen, Jian Wang, Xiaodi Wang, Shumin Han, Xiaokang Chen, Jimin Pi, Kun Yao, Junyu Han, Errui Ding, Jingdong Wang, October 2023
  [openreview] [pdf] [bib] [code]

• Cross-validation for Geospatial Data: Estimating Generalization Performance in Geostatistical Problems

  Jing Wang, Laurel Hopkins, Tyler Hallman, W. Douglas Robinson, Rebecca Hutchinson, October 2023
  [openreview] [pdf] [bib] [code]

• Adaptive Hyperparameter Selection for Differentially Private Gradient Descent

  Dominik Fay, Sindri Magnússon, Jens Sjölund, Mikael Johansson, October 2023
  [openreview] [pdf] [bib]

• Multiscale Causal Structure Learning

  Gabriele D'Acunto, Paolo Di Lorenzo, Sergio Barbarossa, October 2023
  [openreview] [pdf] [bib] [code]

• Dynamic Regret Analysis of Safe Distributed Online Optimization for Convex and Non-convex Problems

  Ting-Jui Chang, Sapana Chaudhary, Dileep Kalathil, Shahin Shahrampour, October 2023
  [openreview] [pdf] [bib]

• Revisiting Image Classifier Training for Improved Certified Robust Defense against Adversarial Patches

  Aniruddha Saha, Shuhua Yu, Mohammad Sadegh Norouzzadeh, Wan-Yi Lin, Chaithanya Kumar Mummadi, October 2023
  [openreview] [pdf] [bib]

• An Optical Control Environment for Benchmarking Reinforcement Learning Algorithms

  ABULIKEMU ABUDUWEILI, Changliu Liu, October 2023
  [openreview] [pdf] [bib] [code]

• Learning-to-defer for sequential medical decision-making under uncertainty

  Shalmali Joshi, Sonali Parbhoo, Finale Doshi-Velez, September 2023
  [openreview] [pdf] [bib]

• Learning domain-specific causal discovery from time series

  Xinyue Wang, Konrad Kording, September 2023
  [openreview] [pdf] [bib] [code]

• Does ‘Deep Learning on a Data Diet’ reproduce? Overall yes, but GraNd at Initialization does not

  Andreas Kirsch, September 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility Written by Expert Reviewer

• Dynamic Subgoal-based Exploration via Bayesian Optimization

  Yijia Wang, Matthias Poloczek, Daniel R. Jiang, September 2023
  [openreview] [pdf] [bib] [code]

• Gated Domain Units for Multi-source Domain Generalization

  Simon Föll, Alina Dubatovka, Eugen Ernst, Siu Lun Chau, Martin Maritsch, Patrik Okanovic, Gudrun Thaeter, Joachim M. Buhmann, Felix Wortmann, Krikamol Muandet, September 2023
  [openreview] [pdf] [bib] [code]

• IBIA: An Incremental Build-Infer-Approximate Framework for Approximate Inference of Partition Function

  Shivani Bathla, Vinita Vasudevan, September 2023
  [openreview] [pdf] [bib]

• Revisiting Sparsity Hunting in Federated Learning: Why does Sparsity Consensus Matter?

  Sara Babakniya, Souvik Kundu, Saurav Prakash, Yue Niu, Salman Avestimehr, September 2023
  [openreview] [pdf] [bib] [code]

• Relating graph auto-encoders to linear models

  Solveig Klepper, Ulrike von Luxburg, September 2023
  [openreview] [pdf] [bib] [code]

• Deep Operator Learning Lessens the Curse of Dimensionality for PDEs

  Ke Chen, Chunmei Wang, Haizhao Yang, September 2023
  [openreview] [pdf] [bib]

• Label Noise-Robust Learning using a Confidence-Based Sieving Strategy

  Reihaneh Torkzadehmahani, Reza Nasirigerdeh, Daniel Rueckert, Georgios Kaissis, September 2023
  [openreview] [pdf] [bib] [code]

• On Perfect Clustering for Gaussian Processes

  Juan Cuesta-Albertos, Subhajit Dutta, September 2023
  [openreview] [pdf] [bib] [code]

• How Reliable is Your Regression Model's Uncertainty Under Real-World Distribution Shifts?

  Fredrik K. Gustafsson, Martin Danelljan, Thomas B. Schön, September 2023
  [openreview] [pdf] [bib] [code]

• RIGNN: A Rationale Perspective for Semi-supervised Open-world Graph Classification

  Xiao Luo, Yusheng Zhao, Zhengyang Mao, Yifang Qin, Wei Ju, Ming Zhang, Yizhou Sun, September 2023
  [openreview] [pdf] [bib]

• SkillS: Adaptive Skill Sequencing for Efficient Temporally-Extended Exploration

  Giulia Vezzani, Dhruva Tirumala, Markus Wulfmeier, Dushyant Rao, Abbas Abdolmaleki, Ben Moran, Tuomas Haarnoja, Jan Humplik, Roland Hafner, Michael Neunert, Claudio Fantacci, Tim Hertweck, Thomas Lampe, Fereshteh Sadeghi, Nicolas Heess, Martin Riedmiller, September 2023
  [openreview] [pdf] [bib]

• Estimating Differential Equations from Temporal Point Processes

  Shuichi Miyazawa, Daichi Mochihashi, September 2023
  [openreview] [pdf] [bib] [code]

• Turning a Curse into a Blessing: Enabling In-Distribution-Data-Free Backdoor Removal via Stabilized Model Inversion

  Si Chen, Yi Zeng, Won Park, Jiachen T. Wang, Xun Chen, Lingjuan Lyu, Zhuoqing Mao, Ruoxi Jia, September 2023
  [openreview] [pdf] [bib] [code]

• Momentum Tracking: Momentum Acceleration for Decentralized Deep Learning on Heterogeneous Data

  Yuki Takezawa, Han Bao, Kenta Niwa, Ryoma Sato, Makoto Yamada, September 2023
  [openreview] [pdf] [bib] [code]

• Optimistic Optimization of Gaussian Process Samples

  Julia Grosse, Cheng Zhang, Philipp Hennig, September 2023
  [openreview] [pdf] [bib] [code]

• Linearized Relative Positional Encoding

  Zhen Qin, Weixuan Sun, Kaiyue Lu, Hui Deng, Dongxu Li, Xiaodong Han, Yuchao Dai, Lingpeng Kong, Yiran Zhong, September 2023
  [openreview] [pdf] [bib] [code]

• DPVIm: Differentially Private Variational Inference Improved

  Joonas Jälkö, Lukas Prediger, Antti Honkela, Samuel Kaski, September 2023
  [openreview] [pdf] [bib]
  Certifications: Written by Expert Reviewer

• RIFLE: Imputation and Robust Inference from Low Order Marginals

  Sina Baharlouei, Sze-Chuan Suen, Meisam Razaviyayn, September 2023
  [openreview] [pdf] [bib] [code]

• Offline Reinforcement Learning with Mixture of Deterministic Policies

  Takayuki Osa, Akinobu Hayashi, Pranav Deo, Naoki Morihira, Takahide Yoshiike, September 2023
  [openreview] [pdf] [bib] [code]

• Stochastic Batch Acquisition: A Simple Baseline for Deep Active Learning

  Andreas Kirsch, Sebastian Farquhar, Parmida Atighehchian, Andrew Jesson, Frédéric Branchaud-Charron, Yarin Gal, September 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• A Survey on Transformers in Reinforcement Learning

  Wenzhe Li, Hao Luo, Zichuan Lin, Chongjie Zhang, Zongqing Lu, Deheng Ye, September 2023
  [openreview] [pdf] [bib]
  Certifications: Survey

• On the Sample Complexity of Lipschitz Constant Estimation

  Julien Walden Huang, Stephen J. Roberts, Jan-Peter Calliess, September 2023
  [openreview] [pdf] [bib]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• Achieving the Pareto Frontier of Regret Minimization and Best Arm Identification in Multi-Armed Bandits

  Zixin Zhong, Wang Chi Cheung, Vincent Tan, September 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• Quantization Robust Federated Learning for Efficient Inference on Heterogeneous Devices

  Kartik Gupta, Marios Fournarakis, Matthias Reisser, Christos Louizos, Markus Nagel, September 2023
  [openreview] [pdf] [bib]

• High Fidelity Neural Audio Compression

  Alexandre Défossez, Jade Copet, Gabriel Synnaeve, Yossi Adi, September 2023
  [openreview] [pdf] [bib]
  Certifications: Reproducibility Featured Event: iclr.cc/ICLR/2024/Journal_Track

• Fair and Useful Cohort Selection

  Konstantina Bairaktari, Paul Tsela Langton, Huy Nguyen, Niklas Smedemark-Margulies, Jonathan Ullman, September 2023
  [openreview] [pdf] [bib]

• Walking Out of the Weisfeiler Leman Hierarchy: Graph Learning Beyond Message Passing

  Jan Tönshoff, Martin Ritzert, Hinrikus Wolf, Martin Grohe, September 2023
  [openreview] [pdf] [bib] [code]

• Global Contrastive Learning for Long-Tailed Classification

  Thong Bach, Anh Tong, Truong Son Hy, Vu Nguyen, Thanh Nguyen-Tang, September 2023
  [openreview] [pdf] [bib] [code]

• Approximating Naive Bayes on Unlabelled Categorical Data

  Cormac Herley, September 2023
  [openreview] [pdf] [bib]

• Weight-balancing fixes and flows for deep learning

  Lawrence K. Saul, September 2023
  [openreview] [pdf] [bib]

• $k$-Mixup Regularization for Deep Learning via Optimal Transport

  Kristjan Greenewald, Anming Gu, Mikhail Yurochkin, Justin Solomon, Edward Chien, September 2023
  [openreview] [pdf] [bib] [code]

• HypUC: Hyperfine Uncertainty Calibration with Gradient- boosted Corrections for Reliable Regression on Imbalanced Electrocardiograms

  Uddeshya Upadhyay, Sairam Bade, Arjun Puranik, Shahir Asfahan, Melwin Babu, Francisco Lopez-Jimenez, Samuel Asirvatham, Ashim Prasad, Ajit Rajasekharan, Samir Awasthi, Rakesh Barve, September 2023
  [openreview] [pdf] [bib]

• AP: Selective Activation for De-sparsifying Pruned Networks

  Shiyu Liu, Rohan Ghosh, Mehul Motani, September 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• TSMixer: An All-MLP Architecture for Time Series Forecast-ing

  Si-An Chen, Chun-Liang Li, Sercan O Arik, Nathanael Christian Yoder, Tomas Pfister, September 2023
  [openreview] [pdf] [bib] [code]

• Revisiting Hidden Representations in Transfer Learning for Medical Imaging

  Dovile Juodelyte, Amelia Jiménez-Sánchez, Veronika Cheplygina, September 2023
  [openreview] [pdf] [bib] [code]

• The Geometry of Mixability

  Armando J Cabrera Pacheco, Robert Williamson, September 2023
  [openreview] [pdf] [bib]

• Neural Causal Structure Discovery from Interventions

  Nan Rosemary Ke, Olexa Bilaniuk, Anirudh Goyal, Stefan Bauer, Hugo Larochelle, Bernhard Schölkopf, Michael Curtis Mozer, Christopher Pal, Yoshua Bengio, September 2023
  [openreview] [pdf] [bib]
  Certifications: Written by Expert Reviewer

• Evaluating Human-Language Model Interaction

  Mina Lee, Megha Srivastava, Amelia Hardy, John Thickstun, Esin Durmus, Ashwin Paranjape, Ines Gerard-Ursin, Xiang Lisa Li, Faisal Ladhak, Frieda Rong, Rose E Wang, Minae Kwon, Joon Sung Park, Hancheng Cao, Tony Lee, Rishi Bommasani, Michael S. Bernstein, Percy Liang, September 2023
  [openreview] [pdf] [bib] [code]

• Benchmarking Continuous Time Models for Predicting Multiple Sclerosis Progression

  Alexander Luke Ian Norcliffe, Lev Proleev, Diana Mincu, F Lee Hartsell, Katherine A Heller, Subhrajit Roy, September 2023
  [openreview] [pdf] [bib]

• Differentially Private Diffusion Models

  Tim Dockhorn, Tianshi Cao, Arash Vahdat, Karsten Kreis, September 2023
  [openreview] [pdf] [bib] [code]

• On the special role of class-selective neurons in early training

  Omkar Ranadive, Nikhil Thakurdesai, Ari S. Morcos, Matthew L Leavitt, Stephane Deny, September 2023
  [openreview] [pdf] [bib] [code]

• Multi-annotator Deep Learning: A Probabilistic Framework for Classification

  Marek Herde, Denis Huseljic, Bernhard Sick, September 2023
  [openreview] [pdf] [bib] [code]

• Learning to Optimize Quasi-Newton Methods

  Isaac Liao, Rumen Dangovski, Jakob Nicolaus Foerster, Marin Soljacic, September 2023
  [openreview] [pdf] [bib] [code]

• Task Weighting in Meta-learning with Trajectory Optimisation

  Cuong C. Nguyen, Thanh-Toan Do, Gustavo Carneiro, September 2023
  [openreview] [pdf] [bib] [code]

• Cyclic and Randomized Stepsizes Invoke Heavier Tails in SGD than Constant Stepsize

  Mert Gurbuzbalaban, Yuanhan Hu, Umut Simsekli, Lingjiong Zhu, September 2023
  [openreview] [pdf] [bib] [code]

• A probabilistic Taylor expansion with Gaussian processes

  Toni Karvonen, Jon Cockayne, Filip Tronarp, Simo Särkkä, September 2023
  [openreview] [pdf] [bib]

• Bridging the Gap Between Target Networks and Functional Regularization

  Alexandre Piché, Valentin Thomas, Joseph Marino, Rafael Pardinas, Gian Maria Marconi, Christopher Pal, Mohammad Emtiyaz Khan, September 2023
  [openreview] [pdf] [bib] [code]

• HERMES: Hybrid Error-corrector Model with inclusion of External Signals for nonstationary fashion time series

  Etienne David, Jean Bellot, Sylvain Le Corff, September 2023
  [openreview] [pdf] [bib] [code]

• Detecting incidental correlation in multimodal learning via latent variable modeling

  Taro Makino, Yixin Wang, Krzysztof J. Geras, Kyunghyun Cho, September 2023
  [openreview] [pdf] [bib] [code]

• Fast Kernel Methods for Generic Lipschitz Losses via $p$-Sparsified Sketches

  Tamim El Ahmad, Pierre Laforgue, Florence d'Alché-Buc, September 2023
  [openreview] [pdf] [bib] [code]

• Single-Pass Contrastive Learning Can Work for Both Homophilic and Heterophilic Graph

  Haonan Wang, Jieyu Zhang, Qi Zhu, Wei Huang, Kenji Kawaguchi, Xiaokui Xiao, September 2023
  [openreview] [pdf] [bib] [code]

• Variational Elliptical Processes

  Maria Margareta Bånkestad, Jens Sjölund, Jalil Taghia, Thomas B. Schön, September 2023
  [openreview] [pdf] [bib] [code]

• Mitigating Confirmation Bias in Semi-supervised Learning via Efficient Bayesian Model Averaging

  Charlotte Loh, Rumen Dangovski, Shivchander Sudalairaj, Seungwook Han, Ligong Han, Leonid Karlinsky, Marin Soljacic, Akash Srivastava, September 2023
  [openreview] [pdf] [bib] [code]

• A Survey on Causal Discovery Methods for I.I.D. and Time Series Data

  Uzma Hasan, Emam Hossain, Md Osman Gani, September 2023
  [openreview] [pdf] [bib]
  Certifications: Survey

• Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent

  Da Yu, Gautam Kamath, Janardhan Kulkarni, Tie-Yan Liu, Jian Yin, Huishuai Zhang, September 2023
  [openreview] [pdf] [bib]

• A DNN Optimizer that Improves over AdaBelief by Suppression of the Adaptive Stepsize Range

  Guoqiang Zhang, Kenta Niwa, W. Bastiaan Kleijn, September 2023
  [openreview] [pdf] [bib] [code]

• Faster Training of Neural ODEs Using Gauß–Legendre Quadrature

  Alexander Luke Ian Norcliffe, Marc Peter Deisenroth, September 2023
  [openreview] [pdf] [bib] [code]

• Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting

  Viraj Uday Prabhu, David Acuna, Rafid Mahmood, Marc T. Law, Yuan-Hong Liao, Judy Hoffman, Sanja Fidler, James Lucas, September 2023
  [openreview] [pdf] [bib]

• Efficient Inference With Model Cascades

  Luzian Lebovitz, Lukas Cavigelli, Michele Magno, Lorenz K Muller, September 2023
  [openreview] [pdf] [bib]

• Semantic Representations of Mathematical Expressions in a Continuous Vector Space

  Neeraj Gangwar, Nickvash Kani, September 2023
  [openreview] [pdf] [bib] [code]

• WOODS: Benchmarks for Out-of-Distribution Generalization in Time Series

  Jean-Christophe Gagnon-Audet, Kartik Ahuja, Mohammad Javad Darvishi Bayazi, Pooneh Mousavi, Guillaume Dumas, Irina Rish, September 2023
  [openreview] [pdf] [bib]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• Representations and Computations in Transformers that Support Generalization on Structured Tasks

  Yuxuan Li, James McClelland, September 2023
  [openreview] [pdf] [bib] [code]

• Causal Parrots: Large Language Models May Talk Causality But Are Not Causal

  Matej Zečević, Moritz Willig, Devendra Singh Dhami, Kristian Kersting, September 2023
  [openreview] [pdf] [bib] [code]

• An Option-Dependent Analysis of Regret Minimization Algorithms in Finite-Horizon Semi-MDP

  Gianluca Drappo, Alberto Maria Metelli, Marcello Restelli, September 2023
  [openreview] [pdf] [bib]

• On Adaptivity in Quantum Testing

  Omar Fawzi, Nicolas Flammarion, Aurélien Garivier, Aadil Oufkir, September 2023
  [openreview] [pdf] [bib]

• Teaching Smaller Language Models To Generalise To Unseen Compositional Questions

  Tim Hartill, Neset TAN, Michael Witbrock, Patricia J. Riddle, August 2023
  [openreview] [pdf] [bib] [code]

• Subgraph Permutation Equivariant Networks

  Joshua Mitton, Roderick Murray-Smith, August 2023
  [openreview] [pdf] [bib]

• About the Cost of Central Privacy in Density Estimation

  Clément Lalanne, Aurélien Garivier, Rémi Gribonval, August 2023
  [openreview] [pdf] [bib]

• Some Remarks on Identifiability of Independent Component Analysis in Restricted Function Classes

  Simon Buchholz, August 2023
  [openreview] [pdf] [bib]

• You Only Transfer What You Share: Intersection-Induced Graph Transfer Learning for Link Prediction

  Wenqing Zheng, Edward W Huang, Nikhil Rao, Zhangyang Wang, Karthik Subbian, August 2023
  [openreview] [pdf] [bib]

• Logistic-Normal Likelihoods for Heteroscedastic Label Noise

  Erik Englesson, Amir Mehrpanah, Hossein Azizpour, August 2023
  [openreview] [pdf] [bib] [code]

• RECLIP: Resource-efficient CLIP by Training with Small Images

  Runze Li, Dahun Kim, Bir Bhanu, Weicheng Kuo, August 2023
  [openreview] [pdf] [bib]

• Reinforcement Learning with Delayed, Composite, and Partially Anonymous Reward

  Washim Uddin Mondal, Vaneet Aggarwal, August 2023
  [openreview] [pdf] [bib]

• Towards Multi-spatiotemporal-scale Generalized PDE Modeling

  Jayesh K Gupta, Johannes Brandstetter, August 2023
  [openreview] [pdf] [bib]

• The Multiquadric Kernel for Moment-Matching Distributional Reinforcement Learning

  Ludvig Killingberg, Helge Langseth, August 2023
  [openreview] [pdf] [bib] [code]

• Nonconvex-nonconcave min-max optimization on Riemannian manifolds

  Andi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao, August 2023
  [openreview] [pdf] [bib]

• Learning to Boost Resilience of Complex Networks via Neural Edge Rewiring

  Shanchao Yang, MA KAILI, Baoxiang Wang, Tianshu Yu, Hongyuan Zha, August 2023
  [openreview] [pdf] [bib] [code]

• Simulate Time-integrated Coarse-grained Molecular Dynamics with Multi-scale Graph Networks

  Xiang Fu, Tian Xie, Nathan J. Rebello, Bradley Olsen, Tommi S. Jaakkola, August 2023
  [openreview] [pdf] [bib] [code]

• Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error

  Ondrej Bohdal, Yongxin Yang, Timothy Hospedales, August 2023
  [openreview] [pdf] [bib] [code]

• Holistic Evaluation of Language Models

  Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Alexander Cosgrove, Christopher D Manning, Christopher Re, Diana Acosta-Navas, Drew Arad Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue WANG, Keshav Santhanam, Laurel Orr, Lucia Zheng, Mert Yuksekgonul, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Andrew Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda, August 2023
  [openreview] [pdf] [bib]
  Certifications: Featured Written by Expert Reviewer Event: iclr.cc/ICLR/2024/Journal_Track

• Understanding convolution on graphs via energies

  Francesco Di Giovanni, James Rowbottom, Benjamin Paul Chamberlain, Thomas Markovich, Michael M. Bronstein, August 2023
  [openreview] [pdf] [bib] [code]

• Diffusion Models for Constrained Domains

  Nic Fishman, Leo Klarner, Valentin De Bortoli, Emile Mathieu, Michael John Hutchinson, August 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• One-Step Distributional Reinforcement Learning

  Mastane Achab, Reda ALAMI, YASSER ABDELAZIZ DAHOU DJILALI, Kirill Fedyanin, Eric Moulines, August 2023
  [openreview] [pdf] [bib] [code]

• Dual Representation Learning for Out-of-distribution Detection

  Zhilin Zhao, Longbing Cao, August 2023
  [openreview] [pdf] [bib] [code]

• Cyclophobic Reinforcement Learning

  Stefan Sylvius Wagner, Peter Arndt, Jan Robine, Stefan Harmeling, August 2023
  [openreview] [pdf] [bib]

• Neural Ordinary Differential Equations for Modeling Epidemic Spreading

  Chrysoula Kosma, Giannis Nikolentzos, George Panagopoulos, Jean-Marc Steyaert, Michalis Vazirgiannis, August 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Featured Written by Expert Reviewer Event: iclr.cc/ICLR/2024/Journal_Track

• Rotation-Invariant Random Features Provide a Strong Baseline for Machine Learning on 3D Point Clouds

  Owen Melia, Eric M Jonas, Rebecca Willett, August 2023
  [openreview] [pdf] [bib]

• Graph Neural Networks for Temporal Graphs: State of the Art, Open Challenges, and Opportunities

  Antonio Longa, Veronica Lachi, Gabriele Santin, Monica Bianchini, Bruno Lepri, Pietro Lio, franco scarselli, Andrea Passerini, August 2023
  [openreview] [pdf] [bib]

• A Systematic Approach to Universal Random Features in Graph Neural Networks

  Billy Joe Franks, Markus Anders, Marius Kloft, Pascal Schweitzer, August 2023
  [openreview] [pdf] [bib] [code]

• FairGrad: Fairness Aware Gradient Descent

  Gaurav Maheshwari, Michaël Perrot, August 2023
  [openreview] [pdf] [bib] [code]

• V1T: large-scale mouse V1 response prediction using a Vision Transformer

  Bryan M. Li, Isabel Maria Cornacchia, Nathalie Rochefort, Arno Onken, August 2023
  [openreview] [pdf] [bib] [code]

• Novel Class Discovery for Long-tailed Recognition

  Chuyu Zhang, Ruijie Xu, Xuming He, August 2023
  [openreview] [pdf] [bib] [code]

• Asymptotic Analysis of Conditioned Stochastic Gradient Descent

  Rémi Leluc, François Portier, August 2023
  [openreview] [pdf] [bib] [code]

• Learned Thresholds Token Merging and Pruning for Vision Transformers

  Maxim Bonnaerens, Joni Dambre, August 2023
  [openreview] [pdf] [bib] [code]

• MaMMUT: A Simple Architecture for Joint Learning for MultiModal Tasks

  Weicheng Kuo, AJ Piergiovanni, Dahun Kim, xiyang luo, Benjamin Caine, Wei Li, Abhijit Ogale, Luowei Zhou, Andrew M. Dai, Zhifeng Chen, Claire Cui, Anelia Angelova, August 2023
  [openreview] [pdf] [bib]

• Chasing Better Deep Image Priors between Over- and Under-parameterization

  Qiming Wu, Xiaohan Chen, Yifan Jiang, Zhangyang Wang, August 2023
  [openreview] [pdf] [bib] [code]

• Federated High-Dimensional Online Decision Making

  Chi-Hua Wang, Wenjie Li, Guang Lin, August 2023
  [openreview] [pdf] [bib]

• Regret Bounds for Satisficing in Multi-Armed Bandit Problems

  Thomas Michel, Hossein Hajiabolhassan, Ronald Ortner, August 2023
  [openreview] [pdf] [bib]

• Using Confounded Data in Latent Model-Based Reinforcement Learning

  Maxime Gasse, Damien GRASSET, Guillaume Gaudron, Pierre-Yves Oudeyer, August 2023
  [openreview] [pdf] [bib] [code]

• Meta-Learning via Classifier(-free) Diffusion Guidance

  Elvis Nava, Seijin Kobayashi, Yifei Yin, Robert K. Katzschmann, Benjamin F Grewe, August 2023
  [openreview] [pdf] [bib] [code]

• Optimizing Learning Rate Schedules for Iterative Pruning of Deep Neural Networks

  Shiyu Liu, Rohan Ghosh, John Chong Min Tan, Mehul Motani, August 2023
  [openreview] [pdf] [bib] [code]

• Foiling Explanations in Deep Neural Networks

  Snir Vitrack Tamam, Raz Lapid, Moshe Sipper, August 2023
  [openreview] [pdf] [bib] [code]

• Long-term Forecasting with TiDE: Time-series Dense Encoder

  Abhimanyu Das, Weihao Kong, Andrew Leach, Shaan K Mathur, Rajat Sen, Rose Yu, August 2023
  [openreview] [pdf] [bib] [code]

• Empirical Limitations of the NTK for Understanding Scaling Laws in Deep Learning

  Nikhil Vyas, Yamini Bansal, Preetum Nakkiran, August 2023
  [openreview] [pdf] [bib]

• Transport Score Climbing: Variational Inference Using Forward KL and Adaptive Neural Transport

  Liyi Zhang, David Blei, Christian A Naesseth, August 2023
  [openreview] [pdf] [bib] [code]

• Distributionally Robust Classification on a Data Budget

  Benjamin Feuer, Ameya Joshi, Minh Pham, Chinmay Hegde, August 2023
  [openreview] [pdf] [bib] [code]

• The ConceptARC Benchmark: Evaluating Understanding and Generalization in the ARC Domain

  Arsenii Kirillovich Moskvichev, Victor Vikram Odouard, Melanie Mitchell, August 2023
  [openreview] [pdf] [bib] [code]

• Adaptive Compression for Communication-Efficient Distributed Training

  Maksim Makarenko, Elnur Gasanov, Abdurakhmon Sadiev, Rustem Islamov, Peter Richtárik, August 2023
  [openreview] [pdf] [bib] [code]

• Expected Worst Case Regret via Stochastic Sequential Covering

  Changlong Wu, Mohsen Heidari, Ananth Grama, Wojciech Szpankowski, August 2023
  [openreview] [pdf] [bib]

• Robust Alzheimer's Progression Modeling using Cross-Domain Self-Supervised Deep Learning

  Saba Dadsetan, Mohsen Hejrati, Shandong Wu, Somaye Hashemifar, August 2023
  [openreview] [pdf] [bib]

• Learning Augmentation Distributions using Transformed Risk Minimization

  Evangelos Chatzipantazis, Stefanos Pertigkiozoglou, Kostas Daniilidis, Edgar Dobriban, August 2023
  [openreview] [pdf] [bib]

• Structured Low-Rank Tensors for Generalized Linear Models

  Batoul Ahmad Taki, Anand Sarwate, Waheed U. Bajwa, August 2023
  [openreview] [pdf] [bib]

• Scalable Stochastic Gradient Riemannian Langevin Dynamics in Non-Diagonal Metrics

  Hanlin Yu, Marcelo Hartmann, Bernardo Williams, Arto Klami, August 2023
  [openreview] [pdf] [bib] [code]

• Towards a Defense Against Federated Backdoor Attacks Under Continuous Training

  Shuaiqi Wang, Jonathan Hayase, Giulia Fanti, Sewoong Oh, August 2023
  [openreview] [pdf] [bib] [code]

• mL-BFGS: A Momentum-based L-BFGS for Distributed Large-scale Neural Network Optimization

  Yue Niu, Zalan Fabian, Sunwoo Lee, Mahdi Soltanolkotabi, Salman Avestimehr, August 2023
  [openreview] [pdf] [bib]

• Mitigating Real-World Distribution Shifts in the Fourier Domain

  Kiran Krishnamachari, See-Kiong Ng, Chuan-Sheng Foo, August 2023
  [openreview] [pdf] [bib]

• Learning representations that are closed-form Monge mapping optimal with application to domain adaptation

  Oliver Struckmeier, Ievgen Redko, Anton Mallasto, Karol Arndt, Markus Heinonen, Ville Kyrki, August 2023
  [openreview] [pdf] [bib] [code]

• Learning from time-dependent streaming data with online stochastic algorithms

  Antoine Godichon-Baggioni, Nicklas Werge, Olivier Wintenberger, August 2023
  [openreview] [pdf] [bib]

• DoCoM: Compressed Decentralized Optimization with Near-Optimal Sample Complexity

  Chung-Yiu Yau, Hoi To Wai, August 2023
  [openreview] [pdf] [bib] [code]

• Neural Monge Map estimation and its applications

  Jiaojiao Fan, Shu Liu, Shaojun Ma, Hao-Min Zhou, Yongxin Chen, July 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• GPS++: Reviving the Art of Message Passing for Molecular Property Prediction

  Dominic Masters, Josef Dean, Kerstin Klaeser, Zhiyi Li, Samuel Maddrell-Mander, Adam Sanders, Hatem Helal, Deniz Beker, Andrew W Fitzgibbon, Shenyang Huang, Ladislav Rampášek, Dominique Beaini, July 2023
  [openreview] [pdf] [bib] [code]

• Tackling Provably Hard Representative Selection via Graph Neural Networks

  Mehran Kazemi, Anton Tsitsulin, Hossein Esfandiari, Mohammadhossein Bateni, Deepak Ramachandran, Bryan Perozzi, Vahab Mirrokni, July 2023
  [openreview] [pdf] [bib] [code]

• Improved Group Robustness via Classifier Retraining on Independent Splits

  Thien Hang Nguyen, Hongyang R. Zhang, Huy Nguyen, July 2023
  [openreview] [pdf] [bib] [code]

• Execution-based Code Generation using Deep Reinforcement Learning

  Parshin Shojaee, Aneesh Jain, Sindhu Tipirneni, Chandan K. Reddy, July 2023
  [openreview] [pdf] [bib] [code]

• TabCBM: Concept-based Interpretable Neural Networks for Tabular Data

  Mateo Espinosa Zarlenga, Zohreh Shams, Michael Edward Nelson, Been Kim, Mateja Jamnik, July 2023
  [openreview] [pdf] [bib] [code]

• Spectral learning of Bernoulli linear dynamical systems models for decision-making

  Iris R Stone, Yotam Sagiv, Il Memming Park, Jonathan W. Pillow, July 2023
  [openreview] [pdf] [bib] [code]

• Self-Supervision is All You Need for Solving Rubik’s Cube

  Kyo Takano, July 2023
  [openreview] [pdf] [bib] [code]

• Towards Better Generalization with Flexible Representation of Multi-Module Graph Neural Networks

  HyunGeun Lee, Kijung Yoon, July 2023
  [openreview] [pdf] [bib]

• Assisting Human Decisions in Document Matching

  Joon Sik Kim, Valerie Chen, Danish Pruthi, Nihar B Shah, Ameet Talwalkar, July 2023
  [openreview] [pdf] [bib] [code]

• Bayesian Quadrature for Neural Ensemble Search

  Saad Hamid, Xingchen Wan, Martin Jørgensen, Binxin Ru, Michael A Osborne, July 2023
  [openreview] [pdf] [bib] [code]

• JiangJun: Mastering Xiangqi by Tackling Non-Transitivity in Two-Player Zero-Sum Games

  Yang Li, Kun Xiong, Yingping Zhang, Jiangcheng Zhu, Stephen Marcus McAleer, Wei Pan, Jun Wang, Zonghong Dai, Yaodong Yang, July 2023
  [openreview] [pdf] [bib] [code]

• Contrastive Attraction and Contrastive Repulsion for Representation Learning

  Huangjie Zheng, Xu Chen, Jiangchao Yao, Hongxia Yang, Chunyuan Li, Ya Zhang, Hao Zhang, Ivor Tsang, Jingren Zhou, Mingyuan Zhou, July 2023
  [openreview] [pdf] [bib] [code]

• Data Augmentation is a Hyperparameter: Cherry-picked Self-Supervision for Unsupervised Anomaly Detection is Creating the Illusion of Success

  Jaemin Yoo, Tiancheng Zhao, Leman Akoglu, July 2023
  [openreview] [pdf] [bib] [code]

• Data Distillation: A Survey

  Noveen Sachdeva, Julian McAuley, July 2023
  [openreview] [pdf] [bib]
  Certifications: Survey

• Catastrophic overfitting can be induced with discriminative non-robust features

  Guillermo Ortiz-Jimenez, Pau de Jorge, Amartya Sanyal, Adel Bibi, Puneet K. Dokania, Pascal Frossard, Grégory Rogez, Philip Torr, July 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Finding and Only Finding Differential Nash Equilibria by Both Pretending to be a Follower

  Xuchan Bao, Guodong Zhang, July 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems

  Fabian Altekrüger, Paul Hagemann, Gabriele Steidl, July 2023
  [openreview] [pdf] [bib]

• A Characteristic Function for Shapley-Value-Based Attribution of Anomaly Scores

  Naoya Takeishi, Yoshinobu Kawahara, July 2023
  [openreview] [pdf] [bib] [code]

• The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science

  Santiago Miret, Kin Long Kelvin Lee, Carmelo Gonzales, Marcel Nassar, Matthew Spellings, July 2023
  [openreview] [pdf] [bib] [code]

• Differentiable Logic Machines

  Matthieu Zimmer, Xuening Feng, Claire Glanois, Zhaohui JIANG, Jianyi Zhang, Paul Weng, Dong Li, Jianye HAO, Wulong Liu, July 2023
  [openreview] [pdf] [bib]

• Vulnerability-Aware Instance Reweighting For Adversarial Training

  Olukorede Fakorede, Ashutosh Kumar Nirala, Modeste Atsague, Jin Tian, July 2023
  [openreview] [pdf] [bib]

• Lifelong Reinforcement Learning with Modulating Masks

  Eseoghene Ben-Iwhiwhu, Saptarshi Nath, Praveen Kumar Pilly, Soheil Kolouri, Andrea Soltoggio, July 2023
  [openreview] [pdf] [bib] [code]

• Semantic Self-adaptation: Enhancing Generalization with a Single Sample

  Sherwin Bahmani, Oliver Hahn, Eduard Zamfir, Nikita Araslanov, Daniel Cremers, Stefan Roth, July 2023
  [openreview] [pdf] [bib] [code]

• Fair Kernel Regression through Cross-Covariance Operators

  Adrian Perez-Suay, Paula Gordaliza, Jean-Michel Loubes, Dino Sejdinovic, Gustau Camps-Valls, July 2023
  [openreview] [pdf] [bib] [code]

• POMRL: No-Regret Learning-to-Plan with Increasing Horizons

  Khimya Khetarpal, Claire Vernade, Brendan O'Donoghue, Satinder Singh, Tom Zahavy, July 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• The Score-Difference Flow for Implicit Generative Modeling

  Romann M. Weber, July 2023
  [openreview] [pdf] [bib]

• Off-Policy Evaluation with Out-of-Sample Guarantees

  Sofia Ek, Dave Zachariah, Fredrik D. Johansson, Peter Stoica, July 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture Models

  Oleg Arenz, Philipp Dahlinger, Zihan Ye, Michael Volpp, Gerhard Neumann, July 2023
  [openreview] [pdf] [bib] [code]

• On the Gradient Formula for learning Generative Models with Regularized Optimal Transport Costs

  Antoine Houdard, Arthur Leclaire, Nicolas Papadakis, Julien Rabin, July 2023
  [openreview] [pdf] [bib]

• Understanding Self-Supervised Pretraining with Part-Aware Representation Learning

  Jie Zhu, Jiyang Qi, Mingyu Ding, Xiaokang Chen, Ping Luo, Xinggang Wang, Wenyu Liu, Leye Wang, Jingdong Wang, July 2023
  [openreview] [pdf] [bib]

• DSpar: An Embarrassingly Simple Strategy for Efficient GNN training and inference via Degree-based Sparsification

  Zirui Liu, Kaixiong Zhou, Zhimeng Jiang, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu, July 2023
  [openreview] [pdf] [bib]

• Efficient Reward Poisoning Attacks on Online Deep Reinforcement Learning

  Yinglun Xu, Qi Zeng, Gagandeep Singh, July 2023
  [openreview] [pdf] [bib]
  Certifications: Featured

• Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations

  Cong Lu, Philip J. Ball, Tim G. J. Rudner, Jack Parker-Holder, Michael A Osborne, Yee Whye Teh, July 2023
  [openreview] [pdf] [bib] [code]

• Towards a More Rigorous Science of Blindspot Discovery in Image Classification Models

  Gregory Plumb, Nari Johnson, Angel Cabrera, Ameet Talwalkar, July 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• On the Predictive Accuracy of Neural Temporal Point Process Models for Continuous-time Event Data

  Tanguy Bosser, Souhaib Ben Taieb, July 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Survey

• Mind the Gap: Mitigating the Distribution Gap in Graph Few-shot Learning

  Chunhui Zhang, Hongfu Liu, Jundong Li, Yanfang Ye, Chuxu Zhang, July 2023
  [openreview] [pdf] [bib]

• Augmented Language Models: a Survey

  Grégoire Mialon, Roberto Dessi, Maria Lomeli, Christoforos Nalmpantis, Ramakanth Pasunuru, Roberta Raileanu, Baptiste Roziere, Timo Schick, Jane Dwivedi-Yu, Asli Celikyilmaz, Edouard Grave, Yann LeCun, Thomas Scialom, July 2023
  [openreview] [pdf] [bib]
  Certifications: Survey

• Black-Box Batch Active Learning for Regression

  Andreas Kirsch, July 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Consistent Collaborative Filtering via Tensor Decomposition

  Shiwen Zhao, Guillermo Sapiro, July 2023
  [openreview] [pdf] [bib] [code]

• Provably Convergent Policy Optimization via Metric-aware Trust Region Methods

  Jun Song, Niao He, Lijun Ding, Chaoyue Zhao, July 2023
  [openreview] [pdf] [bib] [code]

• Adjusting Machine Learning Decisions for Equal Opportunity and Counterfactual Fairness

  Yixin Wang, Dhanya Sridhar, David Blei, July 2023
  [openreview] [pdf] [bib]

• On Average-Case Error Bounds for Kernel-Based Bayesian Quadrature

  Xu Cai, Thanh Lam, Jonathan Scarlett, July 2023
  [openreview] [pdf] [bib] [code]

• Self-Supervised Graph Representation Learning for Neuronal Morphologies

  Marissa A. Weis, Laura Pede, Timo Lüddecke, Alexander S Ecker, July 2023
  [openreview] [pdf] [bib] [code]

• Breaking the Spurious Causality of Conditional Generation via Fairness Intervention with Corrective Sampling

  Junhyun Nam, Sangwoo Mo, Jaeho Lee, Jinwoo Shin, July 2023
  [openreview] [pdf] [bib]

• Stochastic Constrained DRO with a Complexity Independent of Sample Size

  Qi Qi, Jiameng Lyu, Kung-Sik Chan, Er-Wei Bai, Tianbao Yang, July 2023
  [openreview] [pdf] [bib] [code]

• Neural Networks beyond explainability: Selective inference for sequence motifs

  Antoine Villié, Philippe Veber, Yohann De Castro, Laurent Jacob, July 2023
  [openreview] [pdf] [bib] [code]

• Stochastic gradient updates yield deep equilibrium kernels

  Russell Tsuchida, Cheng Soon Ong, July 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Dynamics Adapted Imitation Learning

  Zixuan Liu, Liu Liu, Bingzhe Wu, Lanqing Li, Xueqian Wang, Bo Yuan, Peilin Zhao, July 2023
  [openreview] [pdf] [bib] [code]

• A Proximal Algorithm for Sampling

  Jiaming Liang, Yongxin Chen, July 2023
  [openreview] [pdf] [bib] [code]

• The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus

  Anna Hedström, Philine Lou Bommer, Kristoffer Knutsen Wickstrøm, Wojciech Samek, Sebastian Lapuschkin, Marina MC Höhne, July 2023
  [openreview] [pdf] [bib] [code]

• Calibrating and Improving Graph Contrastive Learning

  MA KAILI, Garry YANG, Han Yang, Yongqiang Chen, James Cheng, July 2023
  [openreview] [pdf] [bib] [code]

• Supervised Knowledge May Hurt Novel Class Discovery Performance

  ZIYUN LI, Jona Otholt, Ben Dai, Di Hu, Christoph Meinel, Haojin Yang, July 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Event: CoLLAs 2023

• DORA: Exploring Outlier Representations in Deep Neural Networks

  Kirill Bykov, Mayukh Deb, Dennis Grinwald, Klaus Robert Muller, Marina MC Höhne, July 2023
  [openreview] [pdf] [bib] [code]

• The Vendi Score: A Diversity Evaluation Metric for Machine Learning

  Dan Friedman, Adji Bousso Dieng, July 2023
  [openreview] [pdf] [bib] [code]

• Contextual Combinatorial Multi-output GP Bandits with Group Constraints

  Sepehr Elahi, Baran Atalar, Sevda Öğüt, Cem Tekin, July 2023
  [openreview] [pdf] [bib] [code]

• Active Acquisition for Multimodal Temporal Data: A Challenging Decision-Making Task

  Jannik Kossen, Cătălina Cangea, Eszter Vértes, Andrew Jaegle, Viorica Patraucean, Ira Ktena, Nenad Tomasev, Danielle Belgrave, June 2023
  [openreview] [pdf] [bib]

• Learning Symbolic Rules for Reasoning in Quasi-Natural Language

  Kaiyu Yang, Jia Deng, June 2023
  [openreview] [pdf] [bib] [code]

• CoCoFL: Communication- and Computation-Aware Federated Learning via Partial NN Freezing and Quantization

  Kilian Pfeiffer, Martin Rapp, Ramin Khalili, Joerg Henkel, June 2023
  [openreview] [pdf] [bib] [code]

• Online Min-max Problems with Non-convexity and Non-stationarity

  Yu Huang, Yuan Cheng, Yingbin Liang, Longbo Huang, June 2023
  [openreview] [pdf] [bib]

• On the Robustness of Dataset Inference

  Sebastian Szyller, Rui Zhang, Jian Liu, N Asokan, June 2023
  [openreview] [pdf] [bib]

• Improving Differentially Private SGD via Randomly Sparsified Gradients

  Junyi Zhu, Matthew B. Blaschko, June 2023
  [openreview] [pdf] [bib] [code]

• SC2 Benchmark: Supervised Compression for Split Computing

  Yoshitomo Matsubara, Ruihan Yang, Marco Levorato, Stephan Mandt, June 2023
  [openreview] [pdf] [bib] [code]

• Inherent Limits on Topology-Based Link Prediction

  Justus Isaiah Hibshman, Tim Weninger, June 2023
  [openreview] [pdf] [bib] [code]

• Instance-Adaptive Video Compression: Improving Neural Codecs by Training on the Test Set

  Ties van Rozendaal, Johann Brehmer, Yunfan Zhang, Reza Pourreza, Auke J. Wiggers, Taco Cohen, June 2023
  [openreview] [pdf] [bib]
  Certifications: Written by Expert Reviewer

• Inversion by Direct Iteration: An Alternative to Denoising Diffusion for Image Restoration

  Mauricio Delbracio, Peyman Milanfar, June 2023
  [openreview] [pdf] [bib]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• Numerical Data Imputation for Multimodal Data Sets: A Probabilistic Nearest-Neighbor Kernel Density Approach

  Florian Lalande, Kenji Doya, June 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility

• Invariant Feature Coding using Tensor Product Representation

  YUSUKE Mukuta, Tatsuya Harada, June 2023
  [openreview] [pdf] [bib]

• Releasing Graph Neural Networks with Differential Privacy Guarantees

  Iyiola Emmanuel Olatunji, Thorben Funke, Megha Khosla, June 2023
  [openreview] [pdf] [bib] [code]

• Sequential Query Encoding for Complex Query Answering on Knowledge Graphs

  Jiaxin Bai, Tianshi Zheng, Yangqiu Song, June 2023
  [openreview] [pdf] [bib] [code]

• TransFool: An Adversarial Attack against Neural Machine Translation Models

  Sahar Sadrizadeh, Ljiljana Dolamic, Pascal Frossard, June 2023
  [openreview] [pdf] [bib]

• An Explicit Expansion of the Kullback-Leibler Divergence along its Fisher-Rao Gradient Flow

  Carles Domingo-Enrich, Aram-Alexandre Pooladian, June 2023
  [openreview] [pdf] [bib]

• Training with Mixed-Precision Floating-Point Assignments

  Wonyeol Lee, Rahul Sharma, Alex Aiken, June 2023
  [openreview] [pdf] [bib]

• Bandwidth Enables Generalization in Quantum Kernel Models

  Abdulkadir Canatar, Evan Peters, Cengiz Pehlevan, Stefan M. Wild, Ruslan Shaydulin, June 2023
  [openreview] [pdf] [bib]

• Privacy-Preserving Energy-Based Generative Models for Marginal Distribution Protection

  Robert E. Tillman, Tucker Balch, Manuela Veloso, June 2023
  [openreview] [pdf] [bib]

• Unsupervised Discovery and Composition of Object Light Fields

  Cameron Omid Smith, Hong-Xing Yu, Sergey Zakharov, Fredo Durand, Joshua B. Tenenbaum, Jiajun Wu, Vincent Sitzmann, June 2023
  [openreview] [pdf] [bib] [code]

• A Kernel Perspective on Behavioural Metrics for Markov Decision Processes

  Pablo Samuel Castro, Tyler Kastner, Prakash Panangaden, Mark Rowland, June 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Pareto Optimization for Active Learning under Out-of-Distribution Data Scenarios

  Xueying Zhan, Zeyu Dai, Qingzhong Wang, Qing Li, Haoyi Xiong, Dejing Dou, Antoni B. Chan, June 2023
  [openreview] [pdf] [bib] [code]

• Predicting Out-of-Domain Generalization with Neighborhood Invariance

  Nathan Hoyen Ng, Neha Hulkund, Kyunghyun Cho, Marzyeh Ghassemi, June 2023
  [openreview] [pdf] [bib]

• Empirical Study on Optimizer Selection for Out-of-Distribution Generalization

  Hiroki Naganuma, Kartik Ahuja, Shiro Takagi, Tetsuya Motokawa, Rio Yokota, Kohta Ishikawa, Ikuro Sato, Ioannis Mitliagkas, June 2023
  [openreview] [pdf] [bib] [code]

• The Eigenlearning Framework: A Conservation Law Perspective on Kernel Ridge Regression and Wide Neural Networks

  James B Simon, Madeline Dickens, Dhruva Karkada, Michael Deweese, June 2023
  [openreview] [pdf] [bib] [code]

• Unsupervised Domain Adaptation via Minimized Joint Error

  Dexuan Zhang, Thomas Westfechtel, Tatsuya Harada, June 2023
  [openreview] [pdf] [bib] [code]

• LEAD: Min-Max Optimization from a Physical Perspective

  Reyhane Askari Hemmat, Amartya Mitra, Guillaume Lajoie, Ioannis Mitliagkas, June 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• On Averaging ROC Curves

  Jack Hogan, Niall M. Adams, June 2023
  [openreview] [pdf] [bib]
  Certifications: Survey

• Undersampling is a Minimax Optimal Robustness Intervention in Nonparametric Classification

  Niladri S. Chatterji, Saminul Haque, Tatsunori Hashimoto, June 2023
  [openreview] [pdf] [bib]

• On the Convergence and Calibration of Deep Learning with Differential Privacy

  Zhiqi Bu, Hua Wang, Zongyu Dai, Qi Long, June 2023
  [openreview] [pdf] [bib] [code]

• A Reproducible and Realistic Evaluation of Partial Domain Adaptation Methods

  Tiago Salvador, Kilian FATRAS, Ioannis Mitliagkas, Adam M Oberman, June 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Event: CoLLAs 2023

• Attentional-Biased Stochastic Gradient Descent

  Qi Qi, Yi Xu, Wotao Yin, Rong Jin, Tianbao Yang, June 2023
  [openreview] [pdf] [bib] [code]

• Reinforcement Teaching

  Calarina Muslimani, Alex Lewandowski, Dale Schuurmans, Matthew E. Taylor, Jun Luo, June 2023
  [openreview] [pdf] [bib] [code]

• Test-Time Adaptation for Visual Document Understanding

  Sayna Ebrahimi, Sercan O Arik, Tomas Pfister, June 2023
  [openreview] [pdf] [bib]

• Learning to Incentivize Improvements from Strategic Agents

  Yatong Chen, Jialu Wang, Yang Liu, June 2023
  [openreview] [pdf] [bib] [code]

• Finding Competence Regions in Domain Generalization

  Jens Müller, Stefan T. Radev, Robert Schmier, Felix Draxler, Carsten Rother, Ullrich Koethe, June 2023
  [openreview] [pdf] [bib] [code]

• Noise-robust Graph Learning by Estimating and Leveraging Pairwise Interactions

  Xuefeng Du, Tian Bian, Yu Rong, Bo Han, Tongliang Liu, Tingyang Xu, Wenbing Huang, Yixuan Li, Junzhou Huang, June 2023
  [openreview] [pdf] [bib] [code]

• 3D-Aware Video Generation

  Sherwin Bahmani, Jeong Joon Park, Despoina Paschalidou, Hao Tang, Gordon Wetzstein, Leonidas Guibas, Luc Van Gool, Radu Timofte, June 2023
  [openreview] [pdf] [bib] [code]

• Bounded Space Differentially Private Quantiles

  Daniel Alabi, Omri Ben-Eliezer, Anamay Chaturvedi, June 2023
  [openreview] [pdf] [bib]

• The Stack: 3 TB of permissively licensed source code

  Denis Kocetkov, Raymond Li, Loubna Ben allal, Jia LI, Chenghao Mou, Yacine Jernite, Margaret Mitchell, Carlos Muñoz Ferrandis, Sean Hughes, Thomas Wolf, Dzmitry Bahdanau, Leandro Von Werra, Harm de Vries, June 2023
  [openreview] [pdf] [bib] [code]

• Exploring the Approximation Capabilities of Multiplicative Neural Networks for Smooth Functions

  Ido Ben-Shaul, Tomer Galanti, Shai Dekel, June 2023
  [openreview] [pdf] [bib]

• Assuming Locally Equal Calibration Errors for Non-Parametric Multiclass Calibration

  Kaspar Valk, Meelis Kull, June 2023
  [openreview] [pdf] [bib] [code]

• Learning Graph Structure from Convolutional Mixtures

  Max Wasserman, Saurabh Sihag, Gonzalo Mateos, Alejandro Ribeiro, June 2023
  [openreview] [pdf] [bib] [code]

• Learning Object-Centric Neural Scattering Functions for Free-viewpoint Relighting and Scene Composition

  Hong-Xing Yu, Michelle Guo, Alireza Fathi, Yen-Yu Chang, Eric Ryan Chan, Ruohan Gao, Thomas Funkhouser, Jiajun Wu, June 2023
  [openreview] [pdf] [bib] [code]

• How to Reuse and Compose Knowledge for a Lifetime of Tasks: A Survey on Continual Learning and Functional Composition

  Jorge A Mendez, ERIC EATON, June 2023
  [openreview] [pdf] [bib]
  Certifications: Survey Event: CoLLAs 2023

• Contextualize Me – The Case for Context in Reinforcement Learning

  Carolin Benjamins, Theresa Eimer, Frederik Schubert, Aditya Mohan, Sebastian Döhler, André Biedenkapp, Bodo Rosenhahn, Frank Hutter, Marius Lindauer, June 2023
  [openreview] [pdf] [bib] [code]

• Multi-dimensional concept discovery (MCD): A unifying framework with completeness guarantees

  Johanna Vielhaben, Stefan Bluecher, Nils Strodthoff, June 2023
  [openreview] [pdf] [bib] [code]

• Dr-Fairness: Dynamic Data Ratio Adjustment for Fair Training on Real and Generated Data

  Yuji Roh, Weili Nie, De-An Huang, Steven Euijong Whang, Arash Vahdat, Anima Anandkumar, June 2023
  [openreview] [pdf] [bib] [code]

• Federated Learning under Covariate Shifts with Generalization Guarantees

  Ali Ramezani-Kebrya, Fanghui Liu, Thomas Pethick, Grigorios Chrysos, Volkan Cevher, June 2023
  [openreview] [pdf] [bib] [code]

• When Does Uncertainty Matter?: Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making

  Sean McGrath, Parth Mehta, Alexandra Zytek, Isaac Lage, Himabindu Lakkaraju, June 2023
  [openreview] [pdf] [bib]

• The Robustness Limits of SoTA Vision Models to Natural Variation

  Mark Ibrahim, Quentin Garrido, Ari S. Morcos, Diane Bouchacourt, June 2023
  [openreview] [pdf] [bib]

• Robust Multi-Agent Reinforcement Learning with State Uncertainty

  Sihong He, Songyang Han, Sanbao Su, Shuo Han, Shaofeng Zou, Fei Miao, June 2023
  [openreview] [pdf] [bib] [code]

• Optimum-statistical Collaboration Towards General and Efficient Black-box Optimization

  Wenjie Li, Chi-Hua Wang, Guang Cheng, Qifan Song, June 2023
  [openreview] [pdf] [bib]

• An Adaptive Half-Space Projection Method for Stochastic Optimization Problems with Group Sparse Regularization

  Yutong Dai, Tianyi Chen, Guanyi Wang, Daniel Robinson, June 2023
  [openreview] [pdf] [bib] [code]

• Causally-guided Regularization of Graph Attention Improves Generalizability

  Alexander P Wu, Thomas Markovich, Bonnie Berger, Nils Yannick Hammerla, Rohit Singh, May 2023
  [openreview] [pdf] [bib]

• Analyzing Deep PAC-Bayesian Learning with Neural Tangent Kernel: Convergence, Analytic Generalization Bound, and Efficient Hyperparameter Selection

  Wei Huang, Chunrui Liu, Yilan Chen, Richard Yi Da Xu, Miao Zhang, Tsui-Wei Weng, May 2023
  [openreview] [pdf] [bib]

• High-Modality Multimodal Transformer: Quantifying Modality & Interaction Heterogeneity for High-Modality Representation Learning

  Paul Pu Liang, Yiwei Lyu, Xiang Fan, Jeffrey Tsaw, Yudong Liu, Shentong Mo, Dani Yogatama, Louis-Philippe Morency, Russ Salakhutdinov, May 2023
  [openreview] [pdf] [bib] [code]

• Learning Interpolations between Boltzmann Densities

  Bálint Máté, François Fleuret, May 2023
  [openreview] [pdf] [bib] [code]

• Retiring $\Delta \text{DP}$: New Distribution-Level Metrics for Demographic Parity

  Xiaotian Han, Zhimeng Jiang, Hongye Jin, Zirui Liu, Na Zou, Qifan Wang, Xia Hu, May 2023
  [openreview] [pdf] [bib] [code]

• Generating Adversarial Examples with Task Oriented Multi-Objective Optimization

  Anh Tuan Bui, Trung Le, He Zhao, Quan Hung Tran, Paul Montague, Dinh Phung, May 2023
  [openreview] [pdf] [bib] [code]

• Aux-Drop: Handling Haphazard Inputs in Online Learning Using Auxiliary Dropouts

  Rohit Agarwal, Deepak Gupta, Alexander Horsch, Dilip K. Prasad, May 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility

• Denise: Deep Robust Principal Component Analysis for Positive Semidefinite Matrices

  Calypso Herrera, Florian Krach, Anastasis Kratsios, Pierre Ruyssen, Josef Teichmann, May 2023
  [openreview] [pdf] [bib]

• Mean-Field Control based Approximation of Multi-Agent Reinforcement Learning in Presence of a Non-decomposable Shared Global State

  Washim Uddin Mondal, Vaneet Aggarwal, Satish Ukkusuri, May 2023
  [openreview] [pdf] [bib] [code]

• Interpretable Mixture of Experts

  Aya Abdelsalam Ismail, Sercan O Arik, Jinsung Yoon, Ankur Taly, Soheil Feizi, Tomas Pfister, May 2023
  [openreview] [pdf] [bib]

• Comparative Generalization Bounds for Deep Neural Networks

  Tomer Galanti, Liane Galanti, Ido Ben-Shaul, May 2023
  [openreview] [pdf] [bib]

• Learning to correct spectral methods for simulating turbulent flows

  Gideon Dresdner, Dmitrii Kochkov, Peter Christian Norgaard, Leonardo Zepeda-Nunez, Jamie Smith, Michael Brenner, Stephan Hoyer, May 2023
  [openreview] [pdf] [bib] [code]

• Cox-Hawkes: doubly stochastic spatiotemporal Poisson processes

  Xenia Miscouridou, Samir Bhatt, George Mohler, Seth Flaxman, Swapnil Mishra, May 2023
  [openreview] [pdf] [bib]

• Personalized Federated Learning: A Unified Framework and Universal Optimization Techniques

  Filip Hanzely, Boxin Zhao, mladen kolar, May 2023
  [openreview] [pdf] [bib] [code]

• Generating Teammates for Training Robust Ad Hoc Teamwork Agents via Best-Response Diversity

  Arrasy Rahman, Elliot Fosong, Ignacio Carlucho, Stefano V Albrecht, May 2023
  [openreview] [pdf] [bib] [code]

• Guillotine Regularization: Why removing layers is needed to improve generalization in Self-Supervised Learning

  Florian Bordes, Randall Balestriero, Quentin Garrido, Adrien Bardes, Pascal Vincent, May 2023
  [openreview] [pdf] [bib]

• Successor Feature Representations

  Chris Reinke, Xavier Alameda-Pineda, May 2023
  [openreview] [pdf] [bib] [code]

• Lightweight Learner for Shared Knowledge Lifelong Learning

  Yunhao Ge, Yuecheng Li, Di Wu, Ao Xu, Adam M. Jones, Amanda Sofie Rios, Iordanis Fostiropoulos, shixian wen, Po-Hsuan Huang, Zachary William Murdock, Gozde Sahin, Shuo Ni, Kiran Lekkala, Sumedh Anand Sontakke, Laurent Itti, May 2023
  [openreview] [pdf] [bib] [code]

• Generalizability of Adversarial Robustness Under Distribution Shifts

  Kumail Alhamoud, Hasan Abed Al Kader Hammoud, Motasem Alfarra, Bernard Ghanem, May 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• Deep Plug-and-Play Clustering with Unknown Number of Clusters

  An Xiao, Hanting Chen, Tianyu Guo, QINGHUA ZHANG, Yunhe Wang, May 2023
  [openreview] [pdf] [bib]

• When to Trust Aggregated Gradients: Addressing Negative Client Sampling in Federated Learning

  Wenkai Yang, Yankai Lin, Guangxiang Zhao, Peng Li, Jie Zhou, Xu Sun, May 2023
  [openreview] [pdf] [bib] [code]

• A Measure of the Complexity of Neural Representations based on Partial Information Decomposition

  David Alexander Ehrlich, Andreas Christian Schneider, Viola Priesemann, Michael Wibral, Abdullah Makkeh, May 2023
  [openreview] [pdf] [bib] [code]

• Know Your Self-supervised Learning: A Survey on Image-based Generative and Discriminative Training

  Utku Ozbulak, Hyun Jung Lee, Beril Boga, Esla Timothy Anzaku, Ho-min Park, Arnout Van Messem, Wesley De Neve, Joris Vankerschaver, May 2023
  [openreview] [pdf] [bib]
  Certifications: Survey

• Trip-ROMA: Self-Supervised Learning with Triplets and Random Mappings

  Wenbin Li, Xuesong Yang, Meihao Kong, Lei Wang, Jing Huo, Yang Gao, Jiebo Luo, May 2023
  [openreview] [pdf] [bib] [code]

• Attacking Perceptual Similarity Metrics

  Abhijay Ghildyal, Feng Liu, May 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• Conditional Permutation Invariant Flows

  Berend Zwartsenberg, Adam Scibior, Matthew Niedoba, Vasileios Lioutas, Justice Sefas, Yunpeng Liu, Setareh Dabiri, Jonathan Wilder Lavington, Trevor Campbell, Frank Wood, May 2023
  [openreview] [pdf] [bib] [code]

• Event Tables for Efficient Experience Replay

  Varun Raj Kompella, Thomas Walsh, Samuel Barrett, Peter R. Wurman, Peter Stone, May 2023
  [openreview] [pdf] [bib]
  Certifications: Event: CoLLAs 2023

• Agent-State Construction with Auxiliary Inputs

  Ruo Yu Tao, Adam White, Marlos C. Machado, May 2023
  [openreview] [pdf] [bib] [code]

• Modelling sequential branching dynamics with a multivariate branching Gaussian process

  Elvijs Sarkans, Sumon Ahmed, Magnus Rattray, Alexis Boukouvalas, May 2023
  [openreview] [pdf] [bib] [code]

• U-NO: U-shaped Neural Operators

  Md Ashiqur Rahman, Zachary E Ross, Kamyar Azizzadenesheli, May 2023
  [openreview] [pdf] [bib] [code]

• Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

  Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R. Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W. Kocurek, Ali Safaya, Ali Tazarv, Alice Xiang, Alicia Parrish, Allen Nie, Aman Hussain, Amanda Askell, Amanda Dsouza, Ambrose Slone, Ameet Rahane, Anantharaman S. Iyer, Anders Johan Andreassen, Andrea Madotto, Andrea Santilli, Andreas Stuhlmüller, Andrew M. Dai, Andrew La, Andrew Lampinen, Andy Zou, Angela Jiang, Angelica Chen, Anh Vuong, Animesh Gupta, Anna Gottardi, Antonio Norelli, Anu Venkatesh, Arash Gholamidavoodi, Arfa Tabassum, Arul Menezes, Arun Kirubarajan, Asher Mullokandov, Ashish Sabharwal, Austin Herrick, Avia Efrat, Aykut Erdem, Ayla Karakaş, B. Ryan Roberts, Bao Sheng Loe, Barret Zoph, Bartłomiej Bojanowski, Batuhan Özyurt, Behnam Hedayatnia, Behnam Neyshabur, Benjamin Inden, Benno Stein, Berk Ekmekci, Bill Yuchen Lin, Blake Howald, Bryan Orinion, Cameron Diao, Cameron Dour, Catherine Stinson, Cedrick Argueta, Cesar Ferri, Chandan Singh, Charles Rathkopf, Chenlin Meng, Chitta Baral, Chiyu Wu, Chris Callison-Burch, Christopher Waites, Christian Voigt, Christopher D Manning, Christopher Potts, Cindy Ramirez, Clara E. Rivera, Clemencia Siro, Colin Raffel, Courtney Ashcraft, Cristina Garbacea, Damien Sileo, Dan Garrette, Dan Hendrycks, Dan Kilman, Dan Roth, C. Daniel Freeman, Daniel Khashabi, Daniel Levy, Daniel Moseguí González, Danielle Perszyk, Danny Hernandez, Danqi Chen, Daphne Ippolito, Dar Gilboa, David Dohan, David Drakard, David Jurgens, Debajyoti Datta, Deep Ganguli, Denis Emelin, Denis Kleyko, Deniz Yuret, Derek Chen, Derek Tam, Dieuwke Hupkes, Diganta Misra, Dilyar Buzan, Dimitri Coelho Mollo, Diyi Yang, Dong-Ho Lee, Dylan Schrader, Ekaterina Shutova, Ekin Dogus Cubuk, Elad Segal, Eleanor Hagerman, Elizabeth Barnes, Elizabeth Donoway, Ellie Pavlick, Emanuele Rodolà, Emma Lam, Eric Chu, Eric Tang, Erkut Erdem, Ernie Chang, Ethan A Chi, Ethan Dyer, Ethan Jerzak, Ethan Kim, Eunice Engefu Manyasi, Evgenii Zheltonozhskii, Fanyue Xia, Fatemeh Siar, Fernando Martínez-Plumed, Francesca Happé, Francois Chollet, Frieda Rong, Gaurav Mishra, Genta Indra Winata, Gerard de Melo, Germán Kruszewski, Giambattista Parascandolo, Giorgio Mariani, Gloria Xinyue Wang, Gonzalo Jaimovitch-Lopez, Gregor Betz, Guy Gur-Ari, Hana Galijasevic, Hannah Kim, Hannah Rashkin, Hannaneh Hajishirzi, Harsh Mehta, Hayden Bogar, Henry Francis Anthony Shevlin, Hinrich Schuetze, Hiromu Yakura, Hongming Zhang, Hugh Mee Wong, Ian Ng, Isaac Noble, Jaap Jumelet, Jack Geissinger, Jackson Kernion, Jacob Hilton, Jaehoon Lee, Jaime Fernández Fisac, James B Simon, James Koppel, James Zheng, James Zou, Jan Kocon, Jana Thompson, Janelle Wingfield, Jared Kaplan, Jarema Radom, Jascha Sohl-Dickstein, Jason Phang, Jason Wei, Jason Yosinski, Jekaterina Novikova, Jelle Bosscher, Jennifer Marsh, Jeremy Kim, Jeroen Taal, Jesse Engel, Jesujoba Alabi, Jiacheng Xu, Jiaming Song, Jillian Tang, Joan Waweru, John Burden, John Miller, John U. Balis, Jonathan Batchelder, Jonathan Berant, Jörg Frohberg, Jos Rozen, Jose Hernandez-Orallo, Joseph Boudeman, Joseph Guerr, Joseph Jones, Joshua B. Tenenbaum, Joshua S. Rule, Joyce Chua, Kamil Kanclerz, Karen Livescu, Karl Krauth, Karthik Gopalakrishnan, Katerina Ignatyeva, Katja Markert, Kaustubh Dhole, Kevin Gimpel, Kevin Omondi, Kory Wallace Mathewson, Kristen Chiafullo, Ksenia Shkaruta, Kumar Shridhar, Kyle McDonell, Kyle Richardson, Laria Reynolds, Leo Gao, Li Zhang, Liam Dugan, Lianhui Qin, Lidia Contreras-Ochando, Louis-Philippe Morency, Luca Moschella, Lucas Lam, Lucy Noble, Ludwig Schmidt, Luheng He, Luis Oliveros-Colón, Luke Metz, Lütfi Kerem Senel, Maarten Bosma, Maarten Sap, Maartje Ter Hoeve, Maheen Farooqi, Manaal Faruqui, Mantas Mazeika, Marco Baturan, Marco Marelli, Marco Maru, Maria Jose Ramirez-Quintana, Marie Tolkiehn, Mario Giulianelli, Martha Lewis, Martin Potthast, Matthew L Leavitt, Matthias Hagen, Mátyás Schubert, Medina Orduna Baitemirova, Melody Arnaud, Melvin McElrath, Michael Andrew Yee, Michael Cohen, Michael Gu, Michael Ivanitskiy, Michael Starritt, Michael Strube, Michał Swędrowski, Michele Bevilacqua, Michihiro Yasunaga, Mihir Kale, Mike Cain, Mimee Xu, Mirac Suzgun, Mitch Walker, Mo Tiwari, Mohit Bansal, Moin Aminnaseri, Mor Geva, Mozhdeh Gheini, Mukund Varma T, Nanyun Peng, Nathan Andrew Chi, Nayeon Lee, Neta Gur-Ari Krakover, Nicholas Cameron, Nicholas Roberts, Nick Doiron, Nicole Martinez, Nikita Nangia, Niklas Deckers, Niklas Muennighoff, Nitish Shirish Keskar, Niveditha S. Iyer, Noah Constant, Noah Fiedel, Nuan Wen, Oliver Zhang, Omar Agha, Omar Elbaghdadi, Omer Levy, Owain Evans, Pablo Antonio Moreno Casares, Parth Doshi, Pascale Fung, Paul Pu Liang, Paul Vicol, Pegah Alipoormolabashi, Peiyuan Liao, Percy Liang, Peter W Chang, Peter Eckersley, Phu Mon Htut, Pinyu Hwang, Piotr Miłkowski, Piyush Patil, Pouya Pezeshkpour, Priti Oli, Qiaozhu Mei, Qing Lyu, Qinlang Chen, Rabin Banjade, Rachel Etta Rudolph, Raefer Gabriel, Rahel Habacker, Ramon Risco, Raphaël Millière, Rhythm Garg, Richard Barnes, Rif A. Saurous, Riku Arakawa, Robbe Raymaekers, Robert Frank, Rohan Sikand, Roman Novak, Roman Sitelew, Ronan Le Bras, Rosanne Liu, Rowan Jacobs, Rui Zhang, Russ Salakhutdinov, Ryan Andrew Chi, Seungjae Ryan Lee, Ryan Stovall, Ryan Teehan, Rylan Yang, Sahib Singh, Saif M. Mohammad, Sajant Anand, Sam Dillavou, Sam Shleifer, Sam Wiseman, Samuel Gruetter, Samuel R. Bowman, Samuel Stern Schoenholz, Sanghyun Han, Sanjeev Kwatra, Sarah A. Rous, Sarik Ghazarian, Sayan Ghosh, Sean Casey, Sebastian Bischoff, Sebastian Gehrmann, Sebastian Schuster, Sepideh Sadeghi, Shadi Hamdan, Sharon Zhou, Shashank Srivastava, Sherry Shi, Shikhar Singh, Shima Asaadi, Shixiang Shane Gu, Shubh Pachchigar, Shubham Toshniwal, Shyam Upadhyay, Shyamolima Shammie Debnath, Siamak Shakeri, Simon Thormeyer, Simone Melzi, Siva Reddy, Sneha Priscilla Makini, Soo-Hwan Lee, Spencer Torene, Sriharsha Hatwar, Stanislas Dehaene, Stefan Divic, Stefano Ermon, Stella Biderman, Stephanie Lin, Stephen Prasad, Steven Piantadosi, Stuart Shieber, Summer Misherghi, Svetlana Kiritchenko, Swaroop Mishra, Tal Linzen, Tal Schuster, Tao Li, Tao Yu, Tariq Ali, Tatsunori Hashimoto, Te-Lin Wu, Théo Desbordes, Theodore Rothschild, Thomas Phan, Tianle Wang, Tiberius Nkinyili, Timo Schick, Timofei Kornev, Titus Tunduny, Tobias Gerstenberg, Trenton Chang, Trishala Neeraj, Tushar Khot, Tyler Shultz, Uri Shaham, Vedant Misra, Vera Demberg, Victoria Nyamai, Vikas Raunak, Vinay Venkatesh Ramasesh, vinay uday prabhu, Vishakh Padmakumar, Vivek Srikumar, William Fedus, William Saunders, William Zhang, Wout Vossen, Xiang Ren, Xiaoyu Tong, Xinran Zhao, Xinyi Wu, Xudong Shen, Yadollah Yaghoobzadeh, Yair Lakretz, Yangqiu Song, Yasaman Bahri, Yejin Choi, Yichi Yang, Yiding Hao, Yifu Chen, Yonatan Belinkov, Yu Hou, Yufang Hou, Yuntao Bai, Zachary Seid, Zhuoye Zhao, Zijian Wang, Zijie J. Wang, Zirui Wang, Ziyi Wu, May 2023
  [openreview] [pdf] [bib] [code]

• Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations

  Xiang Fu, Zhenghao Wu, Wujie Wang, Tian Xie, Sinan Keten, Rafael Gomez-Bombarelli, Tommi Jaakkola, May 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Survey

• Fast&Fair: Training Acceleration and Bias Mitigation for GNNs

  Oyku Deniz Kose, Yanning Shen, May 2023
  [openreview] [pdf] [bib]

• Dual PatchNorm

  Manoj Kumar, Mostafa Dehghani, Neil Houlsby, May 2023
  [openreview] [pdf] [bib]
  Certifications: Written by Expert Reviewer

• Ensembles for Uncertainty Estimation: Benefits of Prior Functions and Bootstrapping

  Vikranth Dwaracherla, Zheng Wen, Ian Osband, Xiuyuan Lu, Seyed Mohammad Asghari, Benjamin Van Roy, May 2023
  [openreview] [pdf] [bib]

• Soft Diffusion: Score Matching with General Corruptions

  Giannis Daras, Mauricio Delbracio, Hossein Talebi, Alex Dimakis, Peyman Milanfar, May 2023
  [openreview] [pdf] [bib]

• Spectral Regularization Allows Data-frugal Learning over Combinatorial Spaces

  Amirali Aghazadeh, Nived Rajaraman, Tony Tu, Kannan Ramchandran, May 2023
  [openreview] [pdf] [bib] [code]

• A Cubic Regularization Approach for Finding Local Minimax Points in Nonconvex Minimax Optimization

  Ziyi Chen, Zhengyang Hu, Qunwei Li, Zhe Wang, Yi Zhou, May 2023
  [openreview] [pdf] [bib] [code]

• Assisted Learning for Organizations with Limited Imbalanced Data

  Cheng Chen, Jiaying Zhou, Jie Ding, Yi Zhou, May 2023
  [openreview] [pdf] [bib]

• Transformer for Partial Differential Equations’ Operator Learning

  Zijie Li, Kazem Meidani, Amir Barati Farimani, May 2023
  [openreview] [pdf] [bib] [code]

• Efficient Model-Based Multi-Agent Mean-Field Reinforcement Learning

  Barna Pásztor, Andreas Krause, Ilija Bogunovic, May 2023
  [openreview] [pdf] [bib]

• Machine Explanations and Human Understanding

  Chacha Chen, Shi Feng, Amit Sharma, Chenhao Tan, May 2023
  [openreview] [pdf] [bib]

• Learning to Look by Self-Prediction

  Matthew Koichi Grimes, Joseph Varughese Modayil, Piotr W Mirowski, Dushyant Rao, Raia Hadsell, May 2023
  [openreview] [pdf] [bib]

• Computationally-efficient initialisation of GPs: The generalised variogram method

  Felipe Tobar, Elsa Cazelles, Taco de Wolff, May 2023
  [openreview] [pdf] [bib] [code]

• Fairness via In-Processing in the Over-parameterized Regime: A Cautionary Tale with MinDiff Loss

  Akshaj Kumar Veldanda, Ivan Brugere, Jiahao Chen, Sanghamitra Dutta, Alan Mishler, Siddharth Garg, May 2023
  [openreview] [pdf] [bib] [code]

• Graph-based Multi-ODE Neural Networks for Spatio-Temporal Traffic Forecasting

  Zibo Liu, Parshin Shojaee, Chandan K. Reddy, May 2023
  [openreview] [pdf] [bib] [code]

• A Stochastic Proximal Polyak Step Size

  Fabian Schaipp, Robert M. Gower, Michael Ulbrich, May 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility

• Fast Treatment Personalization with Latent Bandits in Fixed-Confidence Pure Exploration

  Newton Mwai Kinyanjui, Emil Carlsson, Fredrik D. Johansson, May 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• TimeSeAD: Benchmarking Deep Multivariate Time-Series Anomaly Detection

  Dennis Wagner, Tobias Michels, Florian C.F. Schulz, Arjun Nair, Maja Rudolph, Marius Kloft, May 2023
  [openreview] [pdf] [bib] [code]

• Data Models for Dataset Drift Controls in Machine Learning With Optical Images

  Luis Oala, Marco Aversa, Gabriel Nobis, Kurt Willis, Yoan Neuenschwander, Michèle Buck, Christian Matek, Jerome Extermann, Enrico Pomarico, Wojciech Samek, Roderick Murray-Smith, Christoph Clausen, Bruno Sanguinetti, May 2023
  [openreview] [pdf] [bib] [code]

• Multi-Source Transfer Learning for Deep Model-Based Reinforcement Learning

  Remo Sasso, Matthia Sabatelli, Marco A. Wiering, May 2023
  [openreview] [pdf] [bib] [code]

• Do Vision-Language Pretrained Models Learn Composable Primitive Concepts?

  Tian Yun, Usha Bhalla, Ellie Pavlick, Chen Sun, May 2023
  [openreview] [pdf] [bib] [code]

• A Simulation Environment and Reinforcement Learning Method for Waste Reduction

  Sami Jullien, Mozhdeh Ariannezhad, Paul Groth, Maarten de Rijke, May 2023
  [openreview] [pdf] [bib] [code]

• Understanding Noise-Augmented Training for Randomized Smoothing

  Ambar Pal, Jeremias Sulam, April 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Group Fairness in Reinforcement Learning

  Harsh Satija, Alessandro Lazaric, Matteo Pirotta, Joelle Pineau, April 2023
  [openreview] [pdf] [bib] [code]

• On the Statistical Complexity of Estimation and Testing under Privacy Constraints

  Clément Lalanne, Aurélien Garivier, Rémi Gribonval, April 2023
  [openreview] [pdf] [bib]

• Positive Difference Distribution for Image Outlier Detection using Normalizing Flows and Contrastive Data

  Robert Schmier, Ullrich Koethe, Christoph-Nikolas Straehle, April 2023
  [openreview] [pdf] [bib]

• Uncovering the Representation of Spiking Neural Networks Trained with Surrogate Gradient

  Yuhang Li, Youngeun Kim, Hyoungseob Park, Priyadarshini Panda, April 2023
  [openreview] [pdf] [bib]

• PAC-Bayes Generalisation Bounds for Heavy-Tailed Losses through Supermartingales

  Maxime Haddouche, Benjamin Guedj, April 2023
  [openreview] [pdf] [bib]

• Generalization as Dynamical Robustness--The Role of Riemannian Contraction in Supervised Learning

  Leo Kozachkov, Patrick Wensing, Jean-Jacques Slotine, April 2023
  [openreview] [pdf] [bib]

• Differentially Private Image Classification from Features

  Harsh Mehta, Walid Krichene, Abhradeep Guha Thakurta, Alexey Kurakin, Ashok Cutkosky, April 2023
  [openreview] [pdf] [bib]
  Certifications: Written by Expert Reviewer

• POLTER: Policy Trajectory Ensemble Regularization for Unsupervised Reinforcement Learning

  Frederik Schubert, Carolin Benjamins, Sebastian Döhler, Bodo Rosenhahn, Marius Lindauer, April 2023
  [openreview] [pdf] [bib]

• Proximal Curriculum for Reinforcement Learning Agents

  Georgios Tzannetos, Bárbara Gomes Ribeiro, Parameswaran Kamalaruban, Adish Singla, April 2023
  [openreview] [pdf] [bib] [code]

• Pre-trained Perceptual Features Improve Differentially Private Image Generation

  Frederik Harder, Milad Jalali, Danica J. Sutherland, Mijung Park, April 2023
  [openreview] [pdf] [bib] [code]

• Bridging performance gap between minimal and maximal SVM models

  Ondrej Such, René Fabricius, April 2023
  [openreview] [pdf] [bib] [code]

• Weisfeiler and Leman Go Infinite: Spectral and Combinatorial Pre-Colorings

  Or Feldman, Amit Boyarski, Shai Feldman, Dani Kogan, Avi Mendelson, Chaim Baskin, April 2023
  [openreview] [pdf] [bib]

• Memory-efficient Reinforcement Learning with Value-based Knowledge Consolidation

  Qingfeng Lan, Yangchen Pan, Jun Luo, A. Rupam Mahmood, April 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Event: CoLLAs 2023

• Jacobian-based Causal Discovery with Nonlinear ICA

  Patrik Reizinger, Yash Sharma, Matthias Bethge, Bernhard Schölkopf, Ferenc Huszár, Wieland Brendel, April 2023
  [openreview] [pdf] [bib] [code]

• MASIF: Meta-learned Algorithm Selection using Implicit Fidelity Information

  Tim Ruhkopf, Aditya Mohan, Difan Deng, Alexander Tornede, Frank Hutter, Marius Lindauer, April 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Event: AutoML 2023

• FASTRAIN-GNN: Fast and Accurate Self-Training for Graph Neural Networks

  Amrit Nagarajan, Anand Raghunathan, April 2023
  [openreview] [pdf] [bib] [code]

• Online Optimal Tracking of Linear Systems with Adversarial Disturbances

  Farnaz Adib Yaghmaie, Hamidreza Modares, April 2023
  [openreview] [pdf] [bib] [code]

• Reducing Predictive Feature Suppression in Resource-Constrained Contrastive Image-Caption Retrieval

  Maurits Bleeker, Andrew Yates, Maarten de Rijke, April 2023
  [openreview] [pdf] [bib] [code]

• Deep Double Descent via Smooth Interpolation

  Matteo Gamba, Erik Englesson, Mårten Björkman, Hossein Azizpour, April 2023
  [openreview] [pdf] [bib] [code]

• Bayesian Transformed Gaussian Processes

  Xinran Zhu, Leo Huang, Eric Hans Lee, Cameron Alexander Ibrahim, David Bindel, April 2023
  [openreview] [pdf] [bib] [code]

• A Variational Perspective on Generative Flow Networks

  Heiko Zimmermann, Fredrik Lindsten, Jan-Willem van de Meent, Christian A Naesseth, April 2023
  [openreview] [pdf] [bib] [code]

• Active Learning of Ordinal Embeddings: A User Study on Football Data

  Christoffer Löffler, Kion Fallah, Stefano Fenu, Dario Zanca, Bjoern Eskofier, Christopher John Rozell, Christopher Mutschler, April 2023
  [openreview] [pdf] [bib] [code]

• Differentially private partitioned variational inference

  Mikko A. Heikkilä, Matthew Ashman, Siddharth Swaroop, Richard E Turner, Antti Honkela, April 2023
  [openreview] [pdf] [bib] [code]

• Adaptive patch foraging in deep reinforcement learning agents

  Nathan Wispinski, Andrew Butcher, Kory Wallace Mathewson, Craig S Chapman, Matthew Botvinick, Patrick M. Pilarski, April 2023
  [openreview] [pdf] [bib]

• Private Multi-Task Learning: Formulation and Applications to Federated Learning

  Shengyuan Hu, Steven Wu, Virginia Smith, April 2023
  [openreview] [pdf] [bib] [code]

• Sobolev Spaces, Kernels and Discrepancies over Hyperspheres

  Simon Hubbert, Emilio Porcu, Chris J. Oates, Mark Girolami, April 2023
  [openreview] [pdf] [bib]

• Monotone deep Boltzmann machines

  Zhili Feng, Ezra Winston, J Zico Kolter, April 2023
  [openreview] [pdf] [bib] [code]

• NovelCraft: A Dataset for Novelty Detection and Discovery in Open Worlds

  Patrick Feeney, Sarah Schneider, Panagiotis Lymperopoulos, Liping Liu, Matthias Scheutz, Michael C Hughes, April 2023
  [openreview] [pdf] [bib] [code]

• Integrating Bayesian Network Structure into Residual Flows and Variational Autoencoders

  Jacobie Mouton, Rodney Stephen Kroon, April 2023
  [openreview] [pdf] [bib] [code]

• Neural Collapse: A Review on Modelling Principles and Generalization

  Vignesh Kothapalli, April 2023
  [openreview] [pdf] [bib]

• Unifying physical systems’ inductive biases in neural ODE using dynamics constraints

  Yi Heng Lim, Muhammad Firmansyah Kasim, April 2023
  [openreview] [pdf] [bib] [code]

• Bridging Graph Position Encodings for Transformers with Weighted Graph-Walking Automata

  Patrick Soga, David Chiang, April 2023
  [openreview] [pdf] [bib] [code]

• A Study of Biologically Plausible Neural Network: The Role and Interactions of Brain-Inspired Mechanisms in Continual Learning

  Fahad Sarfraz, Elahe Arani, Bahram Zonooz, April 2023
  [openreview] [pdf] [bib]
  Certifications: Event: CoLLAs 2023

• UncertaINR: Uncertainty Quantification of End-to-End Implicit Neural Representations for Computed Tomography

  Francisca Vasconcelos, Bobby He, Nalini M Singh, Yee Whye Teh, April 2023
  [openreview] [pdf] [bib] [code]

• Training Data Size Induced Double Descent For Denoising Feedforward Neural Networks and the Role of Training Noise

  Rishi Sonthalia, Raj Rao Nadakuditi, April 2023
  [openreview] [pdf] [bib]

• Scalable Deep Compressive Sensing

  Zhonghao Zhang, Yipeng Liu, Xingyu Cao, Fei Wen, Ce Zhu, April 2023
  [openreview] [pdf] [bib]

• A Modulation Layer to Increase Neural Network Robustness Against Data Quality Issues

  Mohamed Abdelhack, Jiaming Zhang, Sandhya Tripathi, Bradley A Fritz, Daniel Felsky, Michael Avidan, Yixin Chen, Christopher Ryan King, April 2023
  [openreview] [pdf] [bib] [code]

• Neural Shape Compiler: A Unified Framework for Transforming between Text, Point Cloud, and Program

  Tiange Luo, Honglak Lee, Justin Johnson, April 2023
  [openreview] [pdf] [bib] [code]

• Can Pruning Improve Certified Robustness of Neural Networks?

  Zhangheng LI, Tianlong Chen, Linyi Li, Bo Li, Zhangyang Wang, April 2023
  [openreview] [pdf] [bib] [code]

• Extended Agriculture-Vision: An Extension of a Large Aerial Image Dataset for Agricultural Pattern Analysis

  Jing Wu, David Pichler, Daniel Marley, Naira Hovakimyan, David A Wilson, Jennifer Hobbs, April 2023
  [openreview] [pdf] [bib] [code]

• Transframer: Arbitrary Frame Prediction with Generative Models

  Charlie Nash, Joao Carreira, Jacob C Walker, Iain Barr, Andrew Jaegle, Mateusz Malinowski, Peter Battaglia, April 2023
  [openreview] [pdf] [bib]

• Explaining Visual Counterfactual Explainers

  Diego Velazquez, Pau Rodriguez, Alexandre Lacoste, Issam H. Laradji, Xavier Roca, Jordi Gonzàlez, April 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility

• Prior and Posterior Networks: A Survey on Evidential Deep Learning Methods For Uncertainty Estimation

  Dennis Thomas Ulmer, Christian Hardmeier, Jes Frellsen, April 2023
  [openreview] [pdf] [bib] [code]

• Estimating the Density Ratio between Distributions with High Discrepancy using Multinomial Logistic Regression

  Akash Srivastava, Seungwook Han, Kai Xu, Benjamin Rhodes, Michael U. Gutmann, April 2023
  [openreview] [pdf] [bib] [code]

• A Revenue Function for Comparison-Based Hierarchical Clustering

  Aishik Mandal, Michaël Perrot, Debarghya Ghoshdastidar, April 2023
  [openreview] [pdf] [bib] [code]

• ChemSpacE: Interpretable and Interactive Chemical Space Exploration

  Yuanqi Du, Xian Liu, Nilay Mahesh Shah, Shengchao Liu, Jieyu Zhang, Bolei Zhou, April 2023
  [openreview] [pdf] [bib] [code]

• A Free Lunch with Influence Functions? An Empirical Evaluation of Influence Functions for Average Treatment Effect Estimation

  Matthew James Vowels, Sina Akbari, Necati Cihan Camgoz, Richard Bowden, April 2023
  [openreview] [pdf] [bib] [code]

• Partition-Based Active Learning for Graph Neural Networks

  Jiaqi Ma, Ziqiao Ma, Joyce Chai, Qiaozhu Mei, April 2023
  [openreview] [pdf] [bib]
  Certifications: Survey

• Clustering using Approximate Nearest Neighbour Oracles

  Enayat Ullah, Harry Lang, Raman Arora, Vladimir Braverman, March 2023
  [openreview] [pdf] [bib]

• Bayesian Optimization with Informative Covariance

  Afonso Eduardo, Michael U. Gutmann, March 2023
  [openreview] [pdf] [bib]

• Turning Normalizing Flows into Monge Maps with Geodesic Gaussian Preserving Flows

  Guillaume Morel, Lucas Drumetz, Simon Benaïchouche, Nicolas Courty, François Rousseau, March 2023
  [openreview] [pdf] [bib] [code]

• Graph Neural Networks Designed for Different Graph Types: A Survey

  Josephine Thomas, Alice Moallemy-Oureh, Silvia Beddar-Wiesing, Clara Holzhüter, March 2023
  [openreview] [pdf] [bib]

• Generalization bounds for Kernel Canonical Correlation Analysis

  Enayat Ullah, Raman Arora, March 2023
  [openreview] [pdf] [bib]

• Learning Identity-Preserving Transformations on Data Manifolds

  Marissa Catherine Connor, Kion Fallah, Christopher John Rozell, March 2023
  [openreview] [pdf] [bib] [code]

• A Halfspace-Mass Depth-Based Method for Adversarial Attack Detection

  Marine Picot, Federica Granese, Guillaume Staerman, Marco Romanelli, Francisco Messina, Pablo Piantanida, Pierre Colombo, March 2023
  [openreview] [pdf] [bib] [code]

• Reusable Options through Gradient-based Meta Learning

  David Kuric, Herke van Hoof, March 2023
  [openreview] [pdf] [bib] [code]

• Containing a spread through sequential learning: to exploit or to explore?

  Xingran Chen, Hesam Nikpey, Jungyeol Kim, Saswati Sarkar, Shirin Saeedi Bidokhti, March 2023
  [openreview] [pdf] [bib] [code]

• Bidirectional View based Consistency Regularization for Semi-Supervised Domain Adaptation

  Yuntao Du, 娟 江, Hongtao Luo, Haiyang Yang, MingCai Chen, Chongjun Wang, March 2023
  [openreview] [pdf] [bib]

• Improving Generalization with Approximate Factored Value Functions

  Shagun Sodhani, Sergey Levine, Amy Zhang, March 2023
  [openreview] [pdf] [bib]
  Certifications: Event: CoLLAs 2023

• FLUID: A Unified Evaluation Framework for Flexible Sequential Data

  Matthew Wallingford, Aditya Kusupati, Keivan Alizadeh-Vahid, Aaron Walsman, Aniruddha Kembhavi, Ali Farhadi, March 2023
  [openreview] [pdf] [bib] [code]

• The Low-Rank Simplicity Bias in Deep Networks

  Minyoung Huh, Hossein Mobahi, Richard Zhang, Brian Cheung, Pulkit Agrawal, Phillip Isola, March 2023
  [openreview] [pdf] [bib]

• Identification of Negative Transfers in Multitask Learning Using Surrogate Models

  Dongyue Li, Huy Nguyen, Hongyang Ryan Zhang, March 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• Multi-objective Bayesian Optimization with Heuristic Objectives for Biomedical and Molecular Data Analysis Workflows

  Alina Selega, Kieran R. Campbell, March 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Event: AutoML 2023

• Parameter Efficient Node Classification on Homophilic Graphs

  Lucas Prieto, Jeroen Den Boef, Paul Groth, Joran Cornelisse, March 2023
  [openreview] [pdf] [bib] [code]

• Towards Better Out-of-Distribution Generalization of Neural Algorithmic Reasoning Tasks

  Sadegh Mahdavi, Kevin Swersky, Thomas Kipf, Milad Hashemi, Christos Thrampoulidis, Renjie Liao, March 2023
  [openreview] [pdf] [bib] [code]

• L-SVRG and L-Katyusha with Adaptive Sampling

  Boxin Zhao, Boxiang Lyu, mladen kolar, March 2023
  [openreview] [pdf] [bib]

• Quantum Policy Iteration via Amplitude Estimation and Grover Search – Towards Quantum Advantage for Reinforcement Learning

  Simon Wiedemann, Daniel Hein, Steffen Udluft, Christian B. Mendl, March 2023
  [openreview] [pdf] [bib]

• Patches Are All You Need?

  Asher Trockman, J Zico Kolter, March 2023
  [openreview] [pdf] [bib]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• Enhancing Diffusion-Based Image Synthesis with Robust Classifier Guidance

  Bahjat Kawar, Roy Ganz, Michael Elad, March 2023
  [openreview] [pdf] [bib]

• Improved Overparametrization Bounds for Global Convergence of SGD for Shallow Neural Networks

  Bartłomiej Polaczyk, Jacek Cyranka, March 2023
  [openreview] [pdf] [bib] [code]

• PRUDEX-Compass: Towards Systematic Evaluation of Reinforcement Learning in Financial Markets

  Shuo Sun, Molei Qin, Xinrun Wang, Bo An, March 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility

• A Unified View of Masked Image Modeling

  Zhiliang Peng, Li Dong, Hangbo Bao, Furu Wei, Qixiang Ye, March 2023
  [openreview] [pdf] [bib] [code]

• How Robust is Your Fairness? Evaluating and Sustaining Fairness under Unseen Distribution Shifts

  Haotao Wang, Junyuan Hong, Jiayu Zhou, Zhangyang Wang, March 2023
  [openreview] [pdf] [bib]

• Leveraging Demonstrations with Latent Space Priors

  Jonas Gehring, Deepak Gopinath, Jungdam Won, Andreas Krause, Gabriel Synnaeve, Nicolas Usunier, March 2023
  [openreview] [pdf] [bib] [code]

• Solving Nonconvex-Nonconcave Min-Max Problems exhibiting Weak Minty Solutions

  Axel Böhm, March 2023
  [openreview] [pdf] [bib] [code]

• Extreme Masking for Learning Instance and Distributed Visual Representations

  Zhirong Wu, Zihang Lai, Xiao Sun, Stephen Lin, March 2023
  [openreview] [pdf] [bib] [code]

• Temperature check: theory and practice for training models with softmax-cross-entropy losses

  Atish Agarwala, Samuel Stern Schoenholz, Jeffrey Pennington, Yann Dauphin, March 2023
  [openreview] [pdf] [bib]

• Fusion of Global and Local Knowledge for Personalized Federated Learning

  Tiansheng Huang, Li Shen, Yan Sun, Weiwei Lin, Dacheng Tao, March 2023
  [openreview] [pdf] [bib] [code]

• Defense Against Reward Poisoning Attacks in Reinforcement Learning

  Kiarash Banihashem, Adish Singla, Goran Radanovic, March 2023
  [openreview] [pdf] [bib]

• Learning Energy Conserving Dynamics Efficiently with Hamiltonian Gaussian Processes

  Magnus Ross, Markus Heinonen, March 2023
  [openreview] [pdf] [bib] [code]

• Continual Learning by Modeling Intra-Class Variation

  Longhui Yu, Tianyang Hu, Lanqing HONG, Zhen Liu, Adrian Weller, Weiyang Liu, March 2023
  [openreview] [pdf] [bib] [code]

• Costs and Benefits of Fair Regression

  Han Zhao, March 2023
  [openreview] [pdf] [bib]

• Transfer Entropy Bottleneck: Learning Sequence to Sequence Information Transfer

  Damjan Kalajdzievski, Ximeng Mao, Pascal Fortier-Poisson, Guillaume Lajoie, Blake Aaron Richards, March 2023
  [openreview] [pdf] [bib] [code]

• Transductive Decoupled Variational Inference for Few-Shot Classification

  Anuj Rajeeva Singh, Hadi Jamali-Rad, March 2023
  [openreview] [pdf] [bib] [code]

• Black-Box Prompt Learning for Pre-trained Language Models

  Shizhe Diao, Zhichao Huang, Ruijia Xu, Xuechun Li, LIN Yong, Xiao Zhou, Tong Zhang, March 2023
  [openreview] [pdf] [bib]

• Numerical Accounting in the Shuffle Model of Differential Privacy

  Antti Koskela, Mikko A. Heikkilä, Antti Honkela, March 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• Image Compression with Product Quantized Masked Image Modeling

  Alaaeldin El-Nouby, Matthew J. Muckley, Karen Ullrich, Ivan Laptev, Jakob Verbeek, Herve Jegou, March 2023
  [openreview] [pdf] [bib]

• Action Poisoning Attacks on Linear Contextual Bandits

  Guanlin Liu, Lifeng Lai, March 2023
  [openreview] [pdf] [bib]

• Mixed effects in machine learning – A flexible mixedML framework to add random effects to supervised machine learning regression

  Pascal Kilian, Sangbeak Ye, Augustin Kelava, March 2023
  [openreview] [pdf] [bib]

• Probing Predictions on OOD Images via Nearest Categories

  Yao-Yuan Yang, Cyrus Rashtchian, Ruslan Salakhutdinov, Kamalika Chaudhuri, March 2023
  [openreview] [pdf] [bib] [code]

• Cheap and Deterministic Inference for Deep State-Space Models of Interacting Dynamical Systems

  Andreas Look, Barbara Rakitsch, Melih Kandemir, Jan Peters, March 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Event: rl-conference.cc/RLC/2024/Journal_Track

• Better Theory for SGD in the Nonconvex World

  Ahmed Khaled, Peter Richtárik, March 2023
  [openreview] [pdf] [bib]
  Certifications: Survey

• Solving a Special Type of Optimal Transport Problem by a Modified Hungarian Algorithm

  Yiling Xie, Yiling Luo, Xiaoming Huo, March 2023
  [openreview] [pdf] [bib]

• AI-SARAH: Adaptive and Implicit Stochastic Recursive Gradient Methods

  Zheng Shi, Abdurakhmon Sadiev, Nicolas Loizou, Peter Richtárik, Martin Takáč, February 2023
  [openreview] [pdf] [bib] [code]

• U-Statistics for Importance-Weighted Variational Inference

  Javier Burroni, Kenta Takatsu, Justin Domke, Daniel Sheldon, February 2023
  [openreview] [pdf] [bib]

• OADAT: Experimental and Synthetic Clinical Optoacoustic Data for Standardized Image Processing

  Firat Ozdemir, Berkan Lafci, Xose Luis Dean-Ben, Daniel Razansky, Fernando Perez-Cruz, February 2023
  [openreview] [pdf] [bib] [code]

• Stacking Diverse Architectures to Improve Machine Translation

  Andrea Schioppa, Nal Kalchbrenner, February 2023
  [openreview] [pdf] [bib] [code]

• Contrastive Search Is What You Need For Neural Text Generation

  Yixuan Su, Nigel Collier, February 2023
  [openreview] [pdf] [bib] [code]

• Separable Self-attention for Mobile Vision Transformers

  Sachin Mehta, Mohammad Rastegari, February 2023
  [openreview] [pdf] [bib] [code]

• A Flexible Nadaraya-Watson Head Can Offer Explainable and Calibrated Classification

  Alan Q. Wang, Mert R. Sabuncu, February 2023
  [openreview] [pdf] [bib] [code]

• Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models

  Juan Lopez Alcaraz, Nils Strodthoff, February 2023
  [openreview] [pdf] [bib] [code]

• Robust Hybrid Learning With Expert Augmentation

  Antoine Wehenkel, Jens Behrmann, Hsiang Hsu, Guillermo Sapiro, Gilles Louppe, Joern-Henrik Jacobsen, February 2023
  [openreview] [pdf] [bib]

• Improved Differentially Private Riemannian Optimization: Fast Sampling and Variance Reduction

  Saiteja Utpala, Andi Han, Pratik Jawanpuria, Bamdev Mishra, February 2023
  [openreview] [pdf] [bib]

• Dirichlet Mechanism for Differentially Private KL Divergence Minimization

  Donlapark Ponnoprat, February 2023
  [openreview] [pdf] [bib] [code]

• Regularized Training of Intermediate Layers for Generative Models for Inverse Problems

  Sean Gunn, Jorio Cocola, PAul HAnd, February 2023
  [openreview] [pdf] [bib] [code]

• Workflow Discovery from Dialogues in the Low Data Regime

  Amine El hattami, Issam H. Laradji, Stefania Raimondo, David Vazquez, Pau Rodriguez, Christopher Pal, February 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• Layerwise Bregman Representation Learning of Neural Networks with Applications to Knowledge Distillation

  Ehsan Amid, Rohan Anil, Christopher Fifty, Manfred K Warmuth, February 2023
  [openreview] [pdf] [bib]

• Learn, Unlearn and Relearn: An Online Learning Paradigm for Deep Neural Networks

  Vijaya Raghavan T Ramkumar, Elahe Arani, Bahram Zonooz, February 2023
  [openreview] [pdf] [bib] [code]

• KRADA: Known-region-aware Domain Alignment for Open-set Domain Adaptation in Semantic Segmentation

  Chenhong Zhou, Feng Liu, Chen Gong, Rongfei Zeng, Tongliang Liu, William Cheung, Bo Han, February 2023
  [openreview] [pdf] [bib] [code]

• Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence

  Diyuan Wu, Vyacheslav Kungurtsev, Marco Mondelli, February 2023
  [openreview] [pdf] [bib]

• DEUP: Direct Epistemic Uncertainty Prediction

  Salem Lahlou, Moksh Jain, Hadi Nekoei, Victor I Butoi, Paul Bertin, Jarrid Rector-Brooks, Maksym Korablyov, Yoshua Bengio, February 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch

  Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan O Arik, Tomas Pfister, February 2023
  [openreview] [pdf] [bib]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• Signed Graph Neural Networks: A Frequency Perspective

  Rahul Singh, Yongxin Chen, February 2023
  [openreview] [pdf] [bib] [code]

• Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models

  Alex Lamb, Riashat Islam, Yonathan Efroni, Aniket Rajiv Didolkar, Dipendra Misra, Dylan J Foster, Lekan P Molu, Rajan Chari, Akshay Krishnamurthy, John Langford, February 2023
  [openreview] [pdf] [bib] [code]

• Beyond Intuition: Rethinking Token Attributions inside Transformers

  Jiamin Chen, Xuhong Li, Lei Yu, Dejing Dou, Haoyi Xiong, February 2023
  [openreview] [pdf] [bib] [code]

• Understanding and Simplifying Architecture Search in Spatio-Temporal Graph Neural Networks

  Zhen Xu, quanming yao, Yong Li, Qiang Yang, February 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Event: AutoML 2023

• Finite-Time Analysis of Decentralized Single-Timescale Actor-Critic

  qijun luo, Xiao Li, February 2023
  [openreview] [pdf] [bib]

• Supervised Feature Selection with Neuron Evolution in Sparse Neural Networks

  Zahra Atashgahi, Xuhao Zhang, Neil Kichler, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Raymond Veldhuis, Decebal Constantin Mocanu, February 2023
  [openreview] [pdf] [bib] [code]

• SolidGen: An Autoregressive Model for Direct B-rep Synthesis

  Pradeep Kumar Jayaraman, Joseph George Lambourne, Nishkrit Desai, Karl Willis, Aditya Sanghi, Nigel J. W. Morris, February 2023
  [openreview] [pdf] [bib]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• Differentially Private Fréchet Mean on the Manifold of Symmetric Positive Definite (SPD) Matrices with log-Euclidean Metric

  Saiteja Utpala, Praneeth Vepakomma, Nina Miolane, February 2023
  [openreview] [pdf] [bib]

• Tailoring to the Tails: Risk Measures for Fine-Grained Tail Sensitivity

  Christian Fröhlich, Robert Williamson, February 2023
  [openreview] [pdf] [bib]

• Controlling Neural Network Smoothness for Neural Algorithmic Reasoning

  David A. Klindt, February 2023
  [openreview] [pdf] [bib] [code]

• Target Propagation via Regularized Inversion for Recurrent Neural Networks

  Vincent Roulet, Zaid Harchaoui, February 2023
  [openreview] [pdf] [bib] [code]

• Bayesian Causal Bandits with Backdoor Adjustment Prior

  Jireh Huang, Qing Zhou, January 2023
  [openreview] [pdf] [bib] [code]

• Accelerated Quality-Diversity through Massive Parallelism

  Bryan Lim, Maxime Allard, Luca Grillotti, Antoine Cully, January 2023
  [openreview] [pdf] [bib] [code]

• Risk Sensitive Dead-end Identification in Safety-Critical Offline Reinforcement Learning

  Taylor W. Killian, Sonali Parbhoo, Marzyeh Ghassemi, January 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Event: rl-conference.cc/RLC/2024/Journal_Track

• BIGRoC: Boosting Image Generation via a Robust Classifier

  Roy Ganz, Michael Elad, January 2023
  [openreview] [pdf] [bib] [code]

• Constrained Parameter Inference as a Principle for Learning

  Nasir Ahmad, Ellen Schrader, Marcel van Gerven, January 2023
  [openreview] [pdf] [bib] [code]

• SMILE: Sample-to-feature Mixup for Efficient Transfer Learning

  Xingjian Li, Haoyi Xiong, Cheng-zhong Xu, Dejing Dou, January 2023
  [openreview] [pdf] [bib] [code]

• Optimal Convergence Rates of Deep Convolutional Neural Networks: Additive Ridge Functions

  Zhiying Fang, Guang Cheng, January 2023
  [openreview] [pdf] [bib]

• Dropped Scheduled Task: Mitigating Negative Transfer in Multi-task Learning using Dynamic Task Dropping

  Aakarsh Malhotra, Mayank Vatsa, Richa Singh, January 2023
  [openreview] [pdf] [bib] [code]

• Revisiting adversarial training for the worst-performing class

  Thomas Pethick, Grigorios Chrysos, Volkan Cevher, January 2023
  [openreview] [pdf] [bib] [code]

• Calibrate and Debias Layer-wise Sampling for Graph Convolutional Networks

  Yifan Chen, Tianning Xu, Dilek Hakkani-Tur, Di Jin, Yun Yang, Ruoqing Zhu, January 2023
  [openreview] [pdf] [bib] [code]

• Online Learning for Prediction via Covariance Fitting: Computation, Performance and Robustness

  Muhammad Osama, Dave Zachariah, Peter Stoica, Thomas B. Schön, January 2023
  [openreview] [pdf] [bib]

• ViViT: Curvature Access Through The Generalized Gauss-Newton’s Low-Rank Structure

  Felix Dangel, Lukas Tatzel, Philipp Hennig, January 2023
  [openreview] [pdf] [bib] [code]

• On a continuous time model of gradient descent dynamics and instability in deep learning

  Mihaela Rosca, Yan Wu, Chongli Qin, Benoit Dherin, January 2023
  [openreview] [pdf] [bib] [code]

• Robustness through Data Augmentation Loss Consistency

  Tianjian Huang, Shaunak Ashish Halbe, Chinnadhurai Sankar, Pooyan Amini, Satwik Kottur, Alborz Geramifard, Meisam Razaviyayn, Ahmad Beirami, January 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Towards Large Scale Transfer Learning for Differentially Private Image Classification

  Harsh Mehta, Abhradeep Guha Thakurta, Alexey Kurakin, Ashok Cutkosky, January 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Gradient-adjusted Incremental Target Propagation Provides Effective Credit Assignment in Deep Neural Networks

  Sander Dalm, Nasir Ahmad, Luca Ambrogioni, Marcel van Gerven, January 2023
  [openreview] [pdf] [bib] [code]

• Proportional Fairness in Federated Learning

  Guojun Zhang, Saber Malekmohammadi, Xi Chen, Yaoliang Yu, January 2023
  [openreview] [pdf] [bib]

• On the Role of Fixed Points of Dynamical Systems in Training Physics-Informed Neural Networks

  Franz M. Rohrhofer, Stefan Posch, Clemens Gößnitzer, Bernhard C Geiger, January 2023
  [openreview] [pdf] [bib] [code]

• VN-Transformer: Rotation-Equivariant Attention for Vector Neurons

  Serge Assaad, Carlton Downey, Rami Al-Rfou', Nigamaa Nayakanti, Benjamin Sapp, January 2023
  [openreview] [pdf] [bib]

• lo-fi: distributed fine-tuning without communication

  Mitchell Wortsman, Suchin Gururangan, Shen Li, Ali Farhadi, Ludwig Schmidt, Michael Rabbat, Ari S. Morcos, January 2023
  [openreview] [pdf] [bib]

• Optimal Threshold Labeling for Ordinal Regression Methods

  Ryoya Yamasaki, January 2023
  [openreview] [pdf] [bib] [code]

• Recognition Models to Learn Dynamics from Partial Observations with Neural ODEs

  Mona Buisson-Fenet, Valery Morgenthaler, Sebastian Trimpe, Florent Di Meglio, January 2023
  [openreview] [pdf] [bib]

• Attention Beats Concatenation for Conditioning Neural Fields

  Daniel Rebain, Mark J. Matthews, Kwang Moo Yi, Gopal Sharma, Dmitry Lagun, Andrea Tagliasacchi, January 2023
  [openreview] [pdf] [bib]

• A Ranking Game for Imitation Learning

  Harshit Sikchi, Akanksha Saran, Wonjoon Goo, Scott Niekum, January 2023
  [openreview] [pdf] [bib] [code]

• Implicit Ensemble Training for Efficient and Robust Multiagent Reinforcement Learning

  Macheng Shen, JONATHAN P HOW, January 2023
  [openreview] [pdf] [bib] [code]

• Named Tensor Notation

  David Chiang, Alexander M Rush, Boaz Barak, January 2023
  [openreview] [pdf] [bib]

• PCPs: Patient Cardiac Prototypes to Probe AI-based Medical Diagnoses, Distill Datasets, and Retrieve Patients

  Dani Kiyasseh, Tingting Zhu, David A. Clifton, January 2023
  [openreview] [pdf] [bib]

• On the infinite-depth limit of finite-width neural networks

  Soufiane Hayou, January 2023
  [openreview] [pdf] [bib]

• Intrinsic Dimension for Large-Scale Geometric Learning

  Maximilian Stubbemann, Tom Hanika, Friedrich Martin Schneider, January 2023
  [openreview] [pdf] [bib] [code]

• Beyond Information Gain: An Empirical Benchmark for Low-Switching-Cost Reinforcement Learning

  Shusheng Xu, Yancheng Liang, Yunfei Li, Simon Shaolei Du, Yi Wu, January 2023
  [openreview] [pdf] [bib] [code]

• DisCo: Improving Compositional Generalization in Visual Reasoning through Distribution Coverage

  Joy Hsu, Jiayuan Mao, Jiajun Wu, January 2023
  [openreview] [pdf] [bib]

• Hidden Heterogeneity: When to Choose Similarity-Based Calibration

  Kiri L. Wagstaff, Thomas G Dietterich, January 2023
  [openreview] [pdf] [bib] [code]

• PolyViT: Co-training Vision Transformers on Images, Videos and Audio

  Valerii Likhosherstov, Anurag Arnab, Krzysztof Marcin Choromanski, Mario Lucic, Yi Tay, Mostafa Dehghani, January 2023
  [openreview] [pdf] [bib] [code]

• GSR: A Generalized Symbolic Regression Approach

  Tony Tohme, Dehong Liu, KAMAL YOUCEF-TOUMI, January 2023
  [openreview] [pdf] [bib]

• Bounding generalization error with input compression: An empirical study with infinite-width networks

  Angus Galloway, Anna Golubeva, Mahmoud Salem, Mihai Nica, Yani Ioannou, Graham W. Taylor, January 2023
  [openreview] [pdf] [bib] [code]

• Investigating Action Encodings in Recurrent Neural Networks in Reinforcement Learning

  Matthew Kyle Schlegel, Volodymyr Tkachuk, Adam M White, Martha White, January 2023
  [openreview] [pdf] [bib] [code]
  Certifications: Event: CoLLAs 2023

• Learning Representations for Pixel-based Control: What Matters and Why?

  Manan Tomar, Utkarsh Aashu Mishra, Amy Zhang, Matthew E. Taylor, January 2023
  [openreview] [pdf] [bib] [code]

• FedDAG: Federated DAG Structure Learning

  Erdun Gao, Junjia Chen, Li Shen, Tongliang Liu, Mingming Gong, Howard Bondell, January 2023
  [openreview] [pdf] [bib] [code]

• Communication-Efficient Distributionally Robust Decentralized Learning

  Matteo Zecchin, Marios Kountouris, David Gesbert, January 2023
  [openreview] [pdf] [bib] [code]

• EdiBERT: a generative model for image editing

  Thibaut Issenhuth, Ugo Tanielian, Jeremie Mary, David Picard, January 2023
  [openreview] [pdf] [bib] [code]

• OpenCon: Open-world Contrastive Learning

  Yiyou Sun, Yixuan Li, January 2023
  [openreview] [pdf] [bib] [code]

• Linking Neural Collapse and L2 Normalization with Improved Out-of-Distribution Detection in Deep Neural Networks

  Jarrod Haas, William Yolland, Bernhard T Rabus, January 2023
  [openreview] [pdf] [bib]

• Euclidean-Norm-Induced Schatten-p Quasi-Norm Regularization for Low-Rank Tensor Completion and Tensor Robust Principal Component Analysis

  Jicong Fan, Lijun Ding, Chengrun Yang, Zhao Zhang, Madeleine Udell, January 2023
  [openreview] [pdf] [bib]

• Benchmarks and Algorithms for Offline Preference-Based Reward Learning

  Daniel Shin, Anca Dragan, Daniel S. Brown, January 2023
  [openreview] [pdf] [bib] [code]

• Fairness and robustness in anti-causal prediction

  Maggie Makar, Alexander D'Amour, January 2023
  [openreview] [pdf] [bib]

• Uncertainty-Based Active Learning for Reading Comprehension

  Jing Wang, Jie Shen, Xiaofei Ma, Andrew Arnold, December 2022
  [openreview] [pdf] [bib] [code]

• A geometrical connection between sparse and low-rank matrices and its application to manifold learning

  Lawrence K. Saul, December 2022
  [openreview] [pdf] [bib]

• Collaborative Algorithms for Online Personalized Mean Estimation

  Mahsa Asadi, Aurélien Bellet, Odalric-Ambrym Maillard, Marc Tommasi, December 2022
  [openreview] [pdf] [bib] [code]

• Indiscriminate Data Poisoning Attacks on Neural Networks

  Yiwei Lu, Gautam Kamath, Yaoliang Yu, December 2022
  [openreview] [pdf] [bib]

• An empirical study of implicit regularization in deep offline RL

  Caglar Gulcehre, Srivatsan Srinivasan, Jakub Sygnowski, Georg Ostrovski, Mehrdad Farajtabar, Matthew Hoffman, Razvan Pascanu, Arnaud Doucet, December 2022
  [openreview] [pdf] [bib]

• On Characterizing the Trade-off in Invariant Representation Learning

  Bashir Sadeghi, Sepehr Dehdashtian, Vishnu Boddeti, December 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• Unsupervised Network Embedding Beyond Homophily

  Zhiqiang Zhong, Guadalupe Gonzalez, Daniele Grattarola, Jun Pang, December 2022
  [openreview] [pdf] [bib]

• Unsupervised Learning of Neurosymbolic Encoders

  Eric Zhan, Jennifer J. Sun, Ann Kennedy, Yisong Yue, Swarat Chaudhuri, December 2022
  [openreview] [pdf] [bib] [code]

• Sequentially learning the topological ordering of directed acyclic graphs with likelihood ratio scores

  Gabriel Ruiz, OSCAR HERNAN MADRID PADILLA, Qing Zhou, December 2022
  [openreview] [pdf] [bib] [code]

• A Snapshot of the Frontiers of Client Selection in Federated Learning

  Gergely Dániel Németh, Miguel Angel Lozano, Novi Quadrianto, Nuria M Oliver, December 2022
  [openreview] [pdf] [bib]
  Certifications: Survey

• Object-aware Cropping for Self-Supervised Learning

  Shlok Kumar Mishra, Anshul Shah, Ankan Bansal, Janit K Anjaria, Abhyuday Narayan Jagannatha, Abhishek Sharma, David Jacobs, Dilip Krishnan, December 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Event: CoLLAs 2023

• Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty

  Thomas George, Guillaume Lajoie, Aristide Baratin, December 2022
  [openreview] [pdf] [bib] [code]

• Fourier Sensitivity and Regularization of Computer Vision Models

  Kiran Krishnamachari, See-Kiong Ng, Chuan-Sheng Foo, December 2022
  [openreview] [pdf] [bib] [code]

• Deconstructing Self-Supervised Monocular Reconstruction: The Design Decisions that Matter

  Jaime Spencer, Chris Russell, Simon Hadfield, Richard Bowden, December 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility

• MVSFormer: Multi-View Stereo by Learning Robust Image Features and Temperature-based Depth

  Chenjie Cao, Xinlin Ren, Yanwei Fu, December 2022
  [openreview] [pdf] [bib] [code]

• Controllable Generative Modeling via Causal Reasoning

  Joey Bose, Ricardo Pio Monti, Aditya Grover, December 2022
  [openreview] [pdf] [bib]

• A Stochastic Optimization Framework for Fair Risk Minimization

  Andrew Lowy, Sina Baharlouei, Rakesh Pavan, Meisam Razaviyayn, Ahmad Beirami, December 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Modeling Bounded Rationality in Multi-Agent Simulations Using Rationally Inattentive Reinforcement Learning

  Tong Mu, Stephan Zheng, Alexander R Trott, December 2022
  [openreview] [pdf] [bib]

• Calibrated Selective Classification

  Adam Fisch, Tommi S. Jaakkola, Regina Barzilay, December 2022
  [openreview] [pdf] [bib] [code]

• Unsupervised Mismatch Localization in Cross-Modal Sequential Data with Application to Mispronunciations Localization

  Wei Wei, Hengguan Huang, Xiangming Gu, Hao Wang, Ye Wang, December 2022
  [openreview] [pdf] [bib]

• GIT: A Generative Image-to-text Transformer for Vision and Language

  Jianfeng Wang, Zhengyuan Yang, Xiaowei Hu, Linjie Li, Kevin Lin, Zhe Gan, Zicheng Liu, Ce Liu, Lijuan Wang, December 2022
  [openreview] [pdf] [bib]

• Concave Utility Reinforcement Learning with Zero-Constraint Violations

  Mridul Agarwal, Qinbo Bai, Vaneet Aggarwal, December 2022
  [openreview] [pdf] [bib]

• Fast and Accurate Spreading Process Temporal Scale Estimation

  Abram Magner, Carolyn S Kaminski, Petko Bogdanov, December 2022
  [openreview] [pdf] [bib] [code]

• Extracting Local Reasoning Chains of Deep Neural Networks

  Haiyan Zhao, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang, December 2022
  [openreview] [pdf] [bib]

• On Sample Complexity of Offline Reinforcement Learning with Deep ReLU Networks in Besov Spaces

  Thanh Nguyen-Tang, Sunil Gupta, Hung Tran-The, Svetha Venkatesh, December 2022
  [openreview] [pdf] [bib]

• Distribution Embedding Networks for Generalization from a Diverse Set of Classification Tasks

  Lang Liu, Mahdi Milani Fard, Sen Zhao, December 2022
  [openreview] [pdf] [bib]

• COIN++: Neural Compression Across Modalities

  Emilien Dupont, Hrushikesh Loya, Milad Alizadeh, Adam Golinski, Yee Whye Teh, Arnaud Doucet, December 2022
  [openreview] [pdf] [bib] [code]

• Systematically and efficiently improving $k$-means initialization by pairwise-nearest-neighbor smoothing

  Carlo Baldassi, December 2022
  [openreview] [pdf] [bib] [code]

• GhostSR: Learning Ghost Features for Efficient Image Super-Resolution

  Ying Nie, Kai Han, Zhenhua Liu, Chuanjian Liu, Yunhe Wang, December 2022
  [openreview] [pdf] [bib] [code]

• DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents

  Kushagra Pandey, Avideep Mukherjee, Piyush Rai, Abhishek Kumar, December 2022
  [openreview] [pdf] [bib] [code]

• On the Origins of the Block Structure Phenomenon in Neural Network Representations

  Thao Nguyen, Maithra Raghu, Simon Kornblith, December 2022
  [openreview] [pdf] [bib]

• Interpretable Node Representation with Attribute Decoding

  Xiaohui Chen, Xi Chen, Liping Liu, December 2022
  [openreview] [pdf] [bib]

• A Unified Domain Adaptation Framework with Distinctive Divergence Analysis

  Zhiri YUAN, Xixu HU, Qi WU, Shumin MA, Cheuk Hang LEUNG, Xin Shen, Yiyan HUANG, December 2022
  [openreview] [pdf] [bib]

• Infinitely wide limits for deep Stable neural networks: sub-linear, linear and super-linear activation functions

  Alberto Bordino, Stefano Favaro, Sandra Fortini, December 2022
  [openreview] [pdf] [bib]

• Counterfactual Learning with Multioutput Deep Kernels

  Alberto Caron, Ioanna Manolopoulou, Gianluca Baio, December 2022
  [openreview] [pdf] [bib]

• Incorporating Sum Constraints into Multitask Gaussian Processes

  Philipp Pilar, Carl Jidling, Thomas B. Schön, Niklas Wahlström, December 2022
  [openreview] [pdf] [bib] [code]

• Degradation Attacks on Certifiably Robust Neural Networks

  Klas Leino, Chi Zhang, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina Pasareanu, November 2022
  [openreview] [pdf] [bib] [code]

• If your data distribution shifts, use self-learning

  Evgenia Rusak, Steffen Schneider, George Pachitariu, Luisa Eck, Peter Vincent Gehler, Oliver Bringmann, Wieland Brendel, Matthias Bethge, November 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• An approximate sampler for energy-based models with divergence diagnostics

  Bryan Eikema, Germán Kruszewski, Christopher R Dance, Hady Elsahar, Marc Dymetman, November 2022
  [openreview] [pdf] [bib] [code]

• A Unified Survey on Anomaly, Novelty, Open-Set, and Out of-Distribution Detection: Solutions and Future Challenges

  Mohammadreza Salehi, Hossein Mirzaei, Dan Hendrycks, Yixuan Li, Mohammad Hossein Rohban, Mohammad Sabokrou, November 2022
  [openreview] [pdf] [bib] [code]

• Bayesian Methods for Constraint Inference in Reinforcement Learning

  Dimitris Papadimitriou, Usman Anwar, Daniel S. Brown, November 2022
  [openreview] [pdf] [bib] [code]

• A Crisis In Simulation-Based Inference? Beware, Your Posterior Approximations Can Be Unfaithful

  Joeri Hermans, Arnaud Delaunoy, François Rozet, Antoine Wehenkel, Volodimir Begy, Gilles Louppe, November 2022
  [openreview] [pdf] [bib] [code]

• On Pseudo-Labeling for Class-Mismatch Semi-Supervised Learning

  Lu Han, Han-Jia Ye, De-Chuan Zhan, November 2022
  [openreview] [pdf] [bib]

• Reinventing Policy Iteration under Time Inconsistency

  Nixie S Lesmana, Huangyuan Su, Chi Seng Pun, November 2022
  [openreview] [pdf] [bib] [code]

• Nonparametric Learning of Two-Layer ReLU Residual Units

  Zhunxuan Wang, Linyun He, Chunchuan Lyu, Shay B Cohen, November 2022
  [openreview] [pdf] [bib] [code]

• Stochastic Douglas-Rachford Splitting for Regularized Empirical Risk Minimization: Convergence, Mini-batch, and Implementation

  Aysegul Bumin, Kejun Huang, November 2022
  [openreview] [pdf] [bib] [code]

• Does Entity Abstraction Help Generative Transformers Reason?

  Nicolas Gontier, Siva Reddy, Christopher Pal, November 2022
  [openreview] [pdf] [bib]

• Complex-Valued Autoencoders for Object Discovery

  Sindy Löwe, Phillip Lippe, Maja Rudolph, Max Welling, November 2022
  [openreview] [pdf] [bib] [code]

• Learning Algorithms for Markovian Bandits:\\Is Posterior Sampling more Scalable than Optimism?

  Nicolas Gast, Bruno Gaujal, Kimang Khun, November 2022
  [openreview] [pdf] [bib] [code]

• Modeling Object Dissimilarity for Deep Saliency Prediction

  Bahar Aydemir, Deblina Bhattacharjee, Tong Zhang, Seungryong Kim, Mathieu Salzmann, Sabine Süsstrunk, November 2022
  [openreview] [pdf] [bib] [code]

• Optimizing Intermediate Representations of Generative Models for Phase Retrieval

  Tobias Uelwer, Sebastian Konietzny, Stefan Harmeling, November 2022
  [openreview] [pdf] [bib]

• Algorithms and Theory for Supervised Gradual Domain Adaptation

  Jing Dong, Shiji Zhou, Baoxiang Wang, Han Zhao, November 2022
  [openreview] [pdf] [bib]

• Teacher’s pet: understanding and mitigating biases in distillation

  Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon, Sanjiv Kumar, November 2022
  [openreview] [pdf] [bib]

• Action Noise in Off-Policy Deep Reinforcement Learning: Impact on Exploration and Performance

  Jakob Hollenstein, Sayantan Auddy, Matteo Saveriano, Erwan Renaudo, Justus Piater, November 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Survey Event: rl-conference.cc/RLC/2024/Journal_Track

• Unifying Approaches in Active Learning and Active Sampling via Fisher Information and Information-Theoretic Quantities

  Andreas Kirsch, Yarin Gal, November 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• An Efficient One-Class SVM for Novelty Detection in IoT

  Kun Yang, Samory Kpotufe, Nick Feamster, November 2022
  [openreview] [pdf] [bib]

• Competition over data: how does data purchase affect users?

  Yongchan Kwon, Tony A Ginart, James Zou, November 2022
  [openreview] [pdf] [bib] [code]

• Diffusion Models for Video Prediction and Infilling

  Tobias Höppe, Arash Mehrjou, Stefan Bauer, Didrik Nielsen, Andrea Dittadi, November 2022
  [openreview] [pdf] [bib]

• Efficient Gradient Flows in Sliced-Wasserstein Space

  Clément Bonet, Nicolas Courty, François Septier, Lucas Drumetz, November 2022
  [openreview] [pdf] [bib] [code]

• Approximate Policy Iteration with Bisimulation Metrics

  Mete Kemertas, Allan Douglas Jepson, November 2022
  [openreview] [pdf] [bib] [code]

• Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images

  Philipp Liznerski, Lukas Ruff, Robert A. Vandermeulen, Billy Joe Franks, Klaus Robert Muller, Marius Kloft, November 2022
  [openreview] [pdf] [bib] [code]

• Mitigating Catastrophic Forgetting in Spiking Neural Networks through Threshold Modulation

  Ilyass Hammouamri, Timothée Masquelier, Dennis George Wilson, November 2022
  [openreview] [pdf] [bib] [code]

• A Generalist Agent

  Scott Reed, Konrad Zolna, Emilio Parisotto, Sergio Gómez Colmenarejo, Alexander Novikov, Gabriel Barth-maron, Mai Giménez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, Tom Eccles, Jake Bruce, Ali Razavi, Ashley Edwards, Nicolas Heess, Yutian Chen, Raia Hadsell, Oriol Vinyals, Mahyar Bordbar, Nando de Freitas, November 2022
  [openreview] [pdf] [bib]
  Certifications: Featured Outstanding Event: iclr.cc/ICLR/2024/Journal_Track

• ZerO Initialization: Initializing Neural Networks with only Zeros and Ones

  Jiawei Zhao, Florian Tobias Schaefer, Anima Anandkumar, November 2022
  [openreview] [pdf] [bib] [code]

• A Rigorous Study Of The Deep Taylor Decomposition

  Leon Sixt, Tim Landgraf, November 2022
  [openreview] [pdf] [bib] [code]

• Convergence of denoising diffusion models under the manifold hypothesis

  Valentin De Bortoli, November 2022
  [openreview] [pdf] [bib]
  Certifications: Written by Expert Reviewer

• Scaling Autoregressive Models for Content-Rich Text-to-Image Generation

  Jiahui Yu, Yuanzhong Xu, Jing Yu Koh, Thang Luong, Gunjan Baid, Zirui Wang, Vijay Vasudevan, Alexander Ku, Yinfei Yang, Burcu Karagol Ayan, Ben Hutchinson, Wei Han, Zarana Parekh, Xin Li, Han Zhang, Jason Baldridge, Yonghui Wu, November 2022
  [openreview] [pdf] [bib]
  Certifications: Featured Event: iclr.cc/ICLR/2024/Journal_Track

• Fail-Safe Adversarial Generative Imitation Learning

  Philipp Geiger, Christoph-Nikolas Straehle, November 2022
  [openreview] [pdf] [bib] [code]

• A Note on "Assessing Generalization of SGD via Disagreement"

  Andreas Kirsch, Yarin Gal, November 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• DHA: End-to-End Joint Optimization of Data Augmentation Policy, Hyper-parameter and Architecture

  kaichen zhou, Lanqing HONG, Shoukang Hu, Fengwei Zhou, Binxin Ru, Jiashi Feng, Zhenguo Li, November 2022
  [openreview] [pdf] [bib] [code]

• Data Leakage in Federated Averaging

  Dimitar Iliev Dimitrov, Mislav Balunovic, Nikola Konstantinov, Martin Vechev, November 2022
  [openreview] [pdf] [bib] [code]

• On the Adversarial Robustness of Vision Transformers

  Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh, November 2022
  [openreview] [pdf] [bib] [code]

• Behind the Machine’s Gaze: Neural Networks with Biologically-inspired Constraints Exhibit Human-like Visual Attention

  Leo Schwinn, Doina Precup, Bjoern Eskofier, Dario Zanca, October 2022
  [openreview] [pdf] [bib] [code]

• Structured Uncertainty in the Observation Space of Variational Autoencoders

  James Langley, Miguel Monteiro, Charles Jones, Nick Pawlowski, Ben Glocker, October 2022
  [openreview] [pdf] [bib] [code]

• Distributed Stochastic Algorithms for High-rate Streaming Principal Component Analysis

  Haroon Raja, Waheed Bajwa, October 2022
  [openreview] [pdf] [bib] [code]

• Benchmarking Progress to Infant-Level Physical Reasoning in AI

  Luca Weihs, Amanda Yuile, Renée Baillargeon, Cynthia Fisher, Gary Marcus, Roozbeh Mottaghi, Aniruddha Kembhavi, October 2022
  [openreview] [pdf] [bib] [code]

• Linear algebra with transformers

  Francois Charton, October 2022
  [openreview] [pdf] [bib]

• INR-V: A Continuous Representation Space for Video-based Generative Tasks

  Bipasha Sen, Aditya Agarwal, Vinay P Namboodiri, C.V. Jawahar, October 2022
  [openreview] [pdf] [bib] [code]

• A Simple Convergence Proof of Adam and Adagrad

  Alexandre Défossez, Leon Bottou, Francis Bach, Nicolas Usunier, October 2022
  [openreview] [pdf] [bib]

• On the Paradox of Certified Training

  Nikola Jovanović, Mislav Balunovic, Maximilian Baader, Martin Vechev, October 2022
  [openreview] [pdf] [bib] [code]

• Time Series Alignment with Global Invariances

  Titouan Vayer, Romain Tavenard, Laetitia Chapel, Rémi Flamary, Nicolas Courty, Yann Soullard, October 2022
  [openreview] [pdf] [bib] [code]

• Explicit Group Sparse Projection with Applications to Deep Learning and NMF

  Riyasat Ohib, Nicolas Gillis, Niccolo Dalmasso, Sameena Shah, Vamsi K. Potluru, Sergey Plis, October 2022
  [openreview] [pdf] [bib] [code]

• Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning

  Baijiong Lin, Feiyang Ye, Yu Zhang, Ivor Tsang, October 2022
  [openreview] [pdf] [bib]

• Direct Molecular Conformation Generation

  Jinhua Zhu, Yingce Xia, Chang Liu, Lijun Wu, Shufang Xie, Yusong Wang, Tong Wang, Tao Qin, Wengang Zhou, Houqiang Li, Haiguang Liu, Tie-Yan Liu, October 2022
  [openreview] [pdf] [bib] [code]

• Symbolic Regression is NP-hard

  Marco Virgolin, Solon P Pissis, October 2022
  [openreview] [pdf] [bib]

• Differentially Private Stochastic Expectation Propagation

  Margarita Vinaroz, Mijung Park, October 2022
  [openreview] [pdf] [bib]

• Practicality of generalization guarantees for unsupervised domain adaptation with neural networks

  Adam Breitholtz, Fredrik Daniel Johansson, October 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• On Noise Abduction for Answering Counterfactual Queries: A Practical Outlook

  Saptarshi Saha, Utpal Garain, October 2022
  [openreview] [pdf] [bib] [code]

• Failure Detection in Medical Image Classification: A Reality Check and Benchmarking Testbed

  Mélanie Bernhardt, Fabio De Sousa Ribeiro, Ben Glocker, October 2022
  [openreview] [pdf] [bib]

• Bridging Offline and Online Experimentation: Constraint Active Search for Deployed Performance Optimization

  Junpei Komiyama, Gustavo Malkomes, Bolong Cheng, Michael McCourt, October 2022
  [openreview] [pdf] [bib]

• Multi-Source Causal Inference Using Control Variates under Outcome Selection Bias

  Wenshuo Guo, Serena Lutong Wang, Peng Ding, Yixin Wang, Michael Jordan, October 2022
  [openreview] [pdf] [bib]

• Identifiable Deep Generative Models via Sparse Decoding

  Gemma Elyse Moran, Dhanya Sridhar, Yixin Wang, David Blei, October 2022
  [openreview] [pdf] [bib] [code]

• Using unsupervised learning to detect broken symmetries, with relevance to searches for parity violation in nature.

  Christopher Gorham Lester, October 2022
  [openreview] [pdf] [bib] [code]

• Integrating Rankings into Quantized Scores in Peer Review

  Yusha Liu, Yichong Xu, Nihar B Shah, Aarti Singh, October 2022
  [openreview] [pdf] [bib]

• Towards Accurate Subgraph Similarity Computation via Neural Graph Pruning

  Linfeng Liu, XU HAN, Dawei Zhou, Liping Liu, October 2022
  [openreview] [pdf] [bib] [code]

• Learning Two-Step Hybrid Policy for Graph-Based Interpretable Reinforcement Learning

  Tongzhou Mu, Kaixiang Lin, Feiyang Niu, Govind Thattai, October 2022
  [openreview] [pdf] [bib]

• Secure Domain Adaptation with Multiple Sources

  Serban Stan, Mohammad Rostami, October 2022
  [openreview] [pdf] [bib]

• Teaching Models to Express Their Uncertainty in Words

  Stephanie Lin, Jacob Hilton, Owain Evans, October 2022
  [openreview] [pdf] [bib] [code]

• On Uncertainty in Deep State Space Models for Model-Based Reinforcement Learning

  Philipp Becker, Gerhard Neumann, October 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Event: rl-conference.cc/RLC/2024/Journal_Track

• The Evolution of Out-of-Distribution Robustness Throughout Fine-Tuning

  Anders Johan Andreassen, Yasaman Bahri, Behnam Neyshabur, Rebecca Roelofs, October 2022
  [openreview] [pdf] [bib]

• Simplifying Node Classification on Heterophilous Graphs with Compatible Label Propagation

  Zhiqiang Zhong, Sergei Ivanov, Jun Pang, October 2022
  [openreview] [pdf] [bib]

• Centroids Matching: an efficient Continual Learning approach operating in the embedding space

  Jary Pomponi, Simone Scardapane, Aurelio Uncini, October 2022
  [openreview] [pdf] [bib] [code]

• Nonstationary Reinforcement Learning with Linear Function Approximation

  Huozhi Zhou, Jinglin Chen, Lav R. Varshney, Ashish Jagmohan, October 2022
  [openreview] [pdf] [bib]

• Enhanced gradient-based MCMC in discrete spaces

  Benjamin Rhodes, Michael U. Gutmann, October 2022
  [openreview] [pdf] [bib]

• Flipped Classroom: Effective Teaching for Time Series Forecasting

  Philipp Teutsch, Patrick Mäder, October 2022
  [openreview] [pdf] [bib] [code]

• Deep Policies for Online Bipartite Matching: A Reinforcement Learning Approach

  Mohammad Ali Alomrani, Reza Moravej, Elias Boutros Khalil, October 2022
  [openreview] [pdf] [bib] [code]

• Generative Adversarial Neural Operators

  Md Ashiqur Rahman, Manuel A Florez, Anima Anandkumar, Zachary E Ross, Kamyar Azizzadenesheli, October 2022
  [openreview] [pdf] [bib] [code]

• Lookback for Learning to Branch

  Prateek Gupta, Elias Boutros Khalil, Didier Chételat, Maxime Gasse, Andrea Lodi, Yoshua Bengio, M. Pawan Kumar, October 2022
  [openreview] [pdf] [bib]
  Certifications: Written by Expert Reviewer

• From Optimization Dynamics to Generalization Bounds via Łojasiewicz Gradient Inequality

  Fusheng Liu, Haizhao Yang, Soufiane Hayou, Qianxiao Li, October 2022
  [openreview] [pdf] [bib] [code]

• Unimodal Likelihood Models for Ordinal Data

  Ryoya Yamasaki, October 2022
  [openreview] [pdf] [bib] [code]

• Differentiable Model Compression via Pseudo Quantization Noise

  Alexandre Défossez, Yossi Adi, Gabriel Synnaeve, October 2022
  [openreview] [pdf] [bib] [code]

• Local Kernel Ridge Regression for Scalable, Interpolating, Continuous Regression

  Mingxuan Han, Chenglong Ye, Jeff Phillips, October 2022
  [openreview] [pdf] [bib]
  Certifications: Written by Expert Reviewer

• Mace: A flexible framework for membership privacy estimation in generative models

  Yixi Xu, Sumit Mukherjee, Xiyang Liu, Shruti Tople, Rahul M Dodhia, Juan M Lavista Ferres, October 2022
  [openreview] [pdf] [bib]

• Fingerprints of Super Resolution Networks

  Jeremy Vonderfecht, Feng Liu, October 2022
  [openreview] [pdf] [bib] [code]

• Online Double Oracle

  Le Cong Dinh, Stephen Marcus McAleer, Zheng Tian, Nicolas Perez-Nieves, Oliver Slumbers, David Henry Mguni, Jun Wang, Haitham Bou Ammar, Yaodong Yang, October 2022
  [openreview] [pdf] [bib] [code]

• Attribute Prediction as Multiple Instance Learning

  Diego Marcos, Aike Potze, Wenjia Xu, Devis Tuia, Zeynep Akata, October 2022
  [openreview] [pdf] [bib] [code]

• Completeness and Coherence Learning for Fast Arbitrary Style Transfer

  Zhijie Wu, Chunjin Song, Guanxiong Chen, Sheng Guo, Weilin Huang, October 2022
  [openreview] [pdf] [bib] [code]

• sigmoidF1: A Smooth F1 Score Surrogate Loss for Multilabel Classification

  Gabriel Bénédict, Hendrik Vincent Koops, Daan Odijk, Maarten de Rijke, October 2022
  [openreview] [pdf] [bib] [code]

• FLEA: Provably Robust Fair Multisource Learning from Unreliable Training Data

  Eugenia Iofinova, Nikola Konstantinov, Christoph H Lampert, October 2022
  [openreview] [pdf] [bib] [code]

• GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets

  Johannes Gasteiger, Muhammed Shuaibi, Anuroop Sriram, Stephan Günnemann, Zachary Ward Ulissi, C. Lawrence Zitnick, Abhishek Das, October 2022
  [openreview] [pdf] [bib] [code]

• MixTailor: Mixed Gradient Aggregation for Robust Learning Against Tailored Attacks

  Ali Ramezani-Kebrya, Iman Tabrizian, Fartash Faghri, Petar Popovski, October 2022
  [openreview] [pdf] [bib] [code]

• LIMIS: Locally Interpretable Modeling using Instance-wise Subsampling

  Jinsung Yoon, Sercan O Arik, Tomas Pfister, September 2022
  [openreview] [pdf] [bib]

• Sparse MoEs meet Efficient Ensembles

  James Urquhart Allingham, Florian Wenzel, Zelda E Mariet, Basil Mustafa, Joan Puigcerver, Neil Houlsby, Ghassen Jerfel, Vincent Fortuin, Balaji Lakshminarayanan, Jasper Snoek, Dustin Tran, Carlos Riquelme Ruiz, Rodolphe Jenatton, September 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• FedShuffle: Recipes for Better Use of Local Work in Federated Learning

  Samuel Horváth, Maziar Sanjabi, Lin Xiao, Peter Richtárik, Michael Rabbat, September 2022
  [openreview] [pdf] [bib]

• Representation Alignment in Neural Networks

  Ehsan Imani, Wei Hu, Martha White, September 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Event: CoLLAs 2023

• Faking Interpolation Until You Make It

  Alasdair Paren, Rudra P. K. Poudel, M. Pawan Kumar, September 2022
  [openreview] [pdf] [bib] [code]

• Ensembles of Classifiers: a Bias-Variance Perspective

  Neha Gupta, Jamie Smith, Ben Adlam, Zelda E Mariet, September 2022
  [openreview] [pdf] [bib]

• GFNet: Geometric Flow Network for 3D Point Cloud Semantic Segmentation

  Haibo Qiu, Baosheng Yu, Dacheng Tao, September 2022
  [openreview] [pdf] [bib] [code]

• Deep Learning for Bayesian Optimization of Scientific Problems with High-Dimensional Structure

  Samuel Kim, Peter Y Lu, Charlotte Loh, Jamie Smith, Jasper Snoek, Marin Soljacic, September 2022
  [openreview] [pdf] [bib] [code]

• Evolving Decomposed Plasticity Rules for Information-Bottlenecked Meta-Learning

  Fan Wang, Hao Tian, Haoyi Xiong, Hua Wu, Jie Fu, Yang Cao, Yu Kang, Haifeng Wang, September 2022
  [openreview] [pdf] [bib] [code]

• Multitask Online Mirror Descent

  Nicolò Cesa-Bianchi, Pierre Laforgue, Andrea Paudice, massimiliano pontil, September 2022
  [openreview] [pdf] [bib]

• Approximating 1-Wasserstein Distance with Trees

  Makoto Yamada, Yuki Takezawa, Ryoma Sato, Han Bao, Zornitsa Kozareva, Sujith Ravi, September 2022
  [openreview] [pdf] [bib] [code]

• Do better ImageNet classifiers assess perceptual similarity better?

  Manoj Kumar, Neil Houlsby, Nal Kalchbrenner, Ekin Dogus Cubuk, September 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Learning Accurate Decision Trees with Bandit Feedback via Quantized Gradient Descent

  Ajaykrishna Karthikeyan, Naman Jain, Nagarajan Natarajan, Prateek Jain, September 2022
  [openreview] [pdf] [bib] [code]

• Probabilistic Autoencoder

  Vanessa M Boehm, Uros Seljak, September 2022
  [openreview] [pdf] [bib] [code]

• Decoder Denoising Pretraining for Semantic Segmentation

  Emmanuel Asiedu Brempong, Simon Kornblith, Ting Chen, Niki Parmar, Matthias Minderer, Mohammad Norouzi, September 2022
  [openreview] [pdf] [bib]

• Can You Win Everything with A Lottery Ticket?

  Tianlong Chen, Zhenyu Zhang, Jun Wu, Randy Huang, Sijia Liu, Shiyu Chang, Zhangyang Wang, September 2022
  [openreview] [pdf] [bib] [code]

• HEAT: Hyperedge Attention Networks

  Dobrik Georgiev Georgiev, Marc Brockschmidt, Miltiadis Allamanis, September 2022
  [openreview] [pdf] [bib] [code]

• On the Near-Optimality of Local Policies in Large Cooperative Multi-Agent Reinforcement Learning

  Washim Uddin Mondal, Vaneet Aggarwal, Satish Ukkusuri, September 2022
  [openreview] [pdf] [bib] [code]

• Exploring Efficient Few-shot Adaptation for Vision Transformers

  Chengming Xu, Siqian Yang, Yabiao Wang, Zhanxiong Wang, Yanwei Fu, Xiangyang Xue, September 2022
  [openreview] [pdf] [bib]

• Weight Expansion: A New Perspective on Dropout and Generalization

  Gaojie Jin, Xinping Yi, Pengfei Yang, Lijun Zhang, Sven Schewe, Xiaowei Huang, September 2022
  [openreview] [pdf] [bib] [code]

• Exploring the Learning Mechanisms of Neural Division Modules

  Bhumika Mistry, Katayoun Farrahi, Jonathon Hare, September 2022
  [openreview] [pdf] [bib] [code]

• Domain Invariant Adversarial Learning

  Matan Levi, Idan Attias, Aryeh Kontorovich, September 2022
  [openreview] [pdf] [bib] [code]

• Momentum Capsule Networks

  Josef Gugglberger, Antonio Rodriguez-sanchez, David Peer, September 2022
  [openreview] [pdf] [bib]

• ANCER: Anisotropic Certification via Sample-wise Volume Maximization

  Francisco Eiras, Motasem Alfarra, Philip Torr, M. Pawan Kumar, Puneet K. Dokania, Bernard Ghanem, Adel Bibi, September 2022
  [openreview] [pdf] [bib] [code]

• On the Choice of Interpolation Scheme for Neural CDEs

  James Morrill, Patrick Kidger, Lingyi Yang, Terry Lyons, September 2022
  [openreview] [pdf] [bib]

• Conformal Prediction Intervals with Temporal Dependence

  Zhen Lin, Shubhendu Trivedi, Jimeng Sun, September 2022
  [openreview] [pdf] [bib] [code]

• Meta-Learning Sparse Compression Networks

  Jonathan Schwarz, Yee Whye Teh, September 2022
  [openreview] [pdf] [bib]

• Estimating Potential Outcome Distributions with Collaborating Causal Networks

  Tianhui Zhou, William E Carson IV, David Carlson, September 2022
  [openreview] [pdf] [bib] [code]

• Sparse Coding with Multi-layer Decoders using Variance Regularization

  Katrina Evtimova, Yann LeCun, August 2022
  [openreview] [pdf] [bib] [code]

• Emergent Abilities of Large Language Models

  Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus, August 2022
  [openreview] [pdf] [bib]
  Certifications: Survey

• Efficient CDF Approximations for Normalizing Flows

  Chandramouli Shama Sastry, Andreas Lehrmann, Marcus A Brubaker, Alexander Radovic, August 2022
  [openreview] [pdf] [bib]

• Unsupervised Dense Information Retrieval with Contrastive Learning

  Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, Edouard Grave, August 2022
  [openreview] [pdf] [bib] [code]

• Equivariant Mesh Attention Networks

  Sourya Basu, Jose Gallego-Posada, Francesco Viganò, James Rowbottom, Taco Cohen, August 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons

  Fangshuo Liao, Anastasios Kyrillidis, August 2022
  [openreview] [pdf] [bib] [code]

• CoCa: Contrastive Captioners are Image-Text Foundation Models

  Jiahui Yu, Zirui Wang, Vijay Vasudevan, Legg Yeung, Mojtaba Seyedhosseini, Yonghui Wu, August 2022
  [openreview] [pdf] [bib]

• Attentive Walk-Aggregating Graph Neural Networks

  Mehmet F Demirel, Shengchao Liu, Siddhant Garg, Zhenmei Shi, Yingyu Liang, August 2022
  [openreview] [pdf] [bib] [code]

• Birds of a Feather Trust Together: Knowing When to Trust a Classifier via Adaptive Neighborhood Aggregation

  Miao Xiong, Shen Li, Wenjie Feng, Ailin Deng, Jihai Zhang, Bryan Hooi, August 2022
  [openreview] [pdf] [bib] [code]

• Optimal Client Sampling for Federated Learning

  Wenlin Chen, Samuel Horváth, Peter Richtárik, August 2022
  [openreview] [pdf] [bib] [code]

• DR-DSGD: A Distributionally Robust Decentralized Learning Algorithm over Graphs

  Chaouki Ben Issaid, Anis Elgabli, Mehdi Bennis, August 2022
  [openreview] [pdf] [bib]

• SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning

  ZHUOWEI WANG, Jing Jiang, Bo Han, Lei Feng, Bo An, Gang Niu, Guodong Long, August 2022
  [openreview] [pdf] [bib] [code]

• SFP: State-free Priors for Exploration in Off-Policy Reinforcement Learning

  Marco Bagatella, Sammy Joe Christen, Otmar Hilliges, August 2022
  [openreview] [pdf] [bib] [code]

• Zero-Shot Learning with Common Sense Knowledge Graphs

  Nihal V. Nayak, Stephen Bach, August 2022
  [openreview] [pdf] [bib] [code]

• Causal Feature Selection via Orthogonal Search

  Ashkan Soleymani, Anant Raj, Stefan Bauer, Bernhard Schölkopf, Michel Besserve, August 2022
  [openreview] [pdf] [bib] [code]

• Finding and Fixing Spurious Patterns with Explanations

  Gregory Plumb, Marco Tulio Ribeiro, Ameet Talwalkar, August 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• High Fidelity Visualization of What Your Self-Supervised Representation Knows About

  Florian Bordes, Randall Balestriero, Pascal Vincent, August 2022
  [openreview] [pdf] [bib] [code]

• The Fundamental Limits of Neural Networks for Interval Certified Robustness

  Matthew B Mirman, Maximilian Baader, Martin Vechev, August 2022
  [openreview] [pdf] [bib]

• TITRATED: Learned Human Driving Behavior without Infractions via Amortized Inference

  Vasileios Lioutas, Adam Scibior, Frank Wood, August 2022
  [openreview] [pdf] [bib]

• No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL

  Han Wang, Archit Sakhadeo, Adam M White, James M Bell, Vincent Liu, Xutong Zhao, Puer Liu, Tadashi Kozuno, Alona Fyshe, Martha White, August 2022
  [openreview] [pdf] [bib]

• Mean-Field Langevin Dynamics : Exponential Convergence and Annealing

  Lénaïc Chizat, August 2022
  [openreview] [pdf] [bib] [code]

• Variational Disentanglement for Domain Generalization

  Yufei Wang, Haoliang Li, Hao Cheng, Bihan Wen, Lap-Pui Chau, Alex Kot, August 2022
  [openreview] [pdf] [bib]

• On Robustness to Missing Video for Audiovisual Speech Recognition

  Oscar Chang, Otavio Braga, Hank Liao, Dmitriy Serdyuk, Olivier Siohan, August 2022
  [openreview] [pdf] [bib]

• Identifying Causal Structure in Dynamical Systems

  Dominik Baumann, Friedrich Solowjow, Karl Henrik Johansson, Sebastian Trimpe, August 2022
  [openreview] [pdf] [bib] [code]

• Understanding AdamW through Proximal Methods and Scale-Freeness

  Zhenxun Zhuang, Mingrui Liu, Ashok Cutkosky, Francesco Orabona, August 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Diagnosing and Fixing Manifold Overfitting in Deep Generative Models

  Gabriel Loaiza-Ganem, Brendan Leigh Ross, Jesse C Cresswell, Anthony L. Caterini, August 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Do ReLU Networks Have An Edge When Approximating Compactly-Supported Functions?

  Anastasis Kratsios, Behnoosh Zamanlooy, August 2022
  [openreview] [pdf] [bib]

• Recurrent networks, hidden states and beliefs in partially observable environments

  Gaspard Lambrechts, Adrien Bolland, Damien Ernst, August 2022
  [openreview] [pdf] [bib]

• Self-supervise, Refine, Repeat: Improving Unsupervised Anomaly Detection

  Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan O Arik, Chen-Yu Lee, Tomas Pfister, August 2022
  [openreview] [pdf] [bib]

• A Comprehensive Study of Real-Time Object Detection Networks Across Multiple Domains: A Survey

  Elahe Arani, Shruthi Gowda, Ratnajit Mukherjee, Omar Magdy, Senthilkumar Sockalingam Kathiresan, Bahram Zonooz, August 2022
  [openreview] [pdf] [bib]
  Certifications: Survey

• Domain-invariant Feature Exploration for Domain Generalization

  Wang Lu, Jindong Wang, Haoliang Li, Yiqiang Chen, Xing Xie, August 2022
  [openreview] [pdf] [bib] [code]

• Stable and Interpretable Unrolled Dictionary Learning

  Bahareh Tolooshams, Demba E. Ba, August 2022
  [openreview] [pdf] [bib] [code]

• Exploring Generative Neural Temporal Point Process

  Haitao Lin, Lirong Wu, Guojiang Zhao, Liu Pai, Stan Z. Li, August 2022
  [openreview] [pdf] [bib] [code]

• Improving the Trainability of Deep Neural Networks through Layerwise Batch-Entropy Regularization

  David Peer, Bart Keulen, Sebastian Stabinger, Justus Piater, Antonio Rodriguez-sanchez, August 2022
  [openreview] [pdf] [bib] [code]

• Online Coresets for Parameteric and Non-Parametric Bregman Clustering

  Supratim Shit, Anirban Dasgupta, Rachit Chhaya, Jayesh Choudhari, August 2022
  [openreview] [pdf] [bib]

• Max-Affine Spline Insights Into Deep Network Pruning

  Haoran You, Randall Balestriero, Zhihan Lu, Yutong Kou, Huihong Shi, Shunyao Zhang, Shang Wu, Yingyan Lin, Richard Baraniuk, August 2022
  [openreview] [pdf] [bib]

• Did I do that? Blame as a means to identify controlled effects in reinforcement learning

  Oriol Corcoll, Youssef Sherif Mansour Mohamed, Raul Vicente, August 2022
  [openreview] [pdf] [bib]

• QuaRL: Quantization for Fast and Environmentally Sustainable Reinforcement Learning

  Srivatsan Krishnan, Max Lam, Sharad Chitlangia, Zishen Wan, Gabriel Barth-maron, Aleksandra Faust, Vijay Janapa Reddi, July 2022
  [openreview] [pdf] [bib] [code]

• NeSF: Neural Semantic Fields for Generalizable Semantic Segmentation of 3D Scenes

  Suhani Vora, Noha Radwan, Klaus Greff, Henning Meyer, Kyle Genova, Mehdi S. M. Sajjadi, Etienne Pot, Andrea Tagliasacchi, Daniel Duckworth, July 2022
  [openreview] [pdf] [bib] [code]

• Learning to Switch Among Agents in a Team via 2-Layer Markov Decision Processes

  Vahid Balazadeh, Abir De, Adish Singla, Manuel Gomez Rodriguez, July 2022
  [openreview] [pdf] [bib] [code]

• A Self-Supervised Framework for Function Learning and Extrapolation

  Simon Segert, Jonathan Cohen, July 2022
  [openreview] [pdf] [bib] [code]

• Deep Classifiers with Label Noise Modeling and Distance Awareness

  Vincent Fortuin, Mark Collier, Florian Wenzel, James Urquhart Allingham, Jeremiah Zhe Liu, Dustin Tran, Balaji Lakshminarayanan, Jesse Berent, Rodolphe Jenatton, Effrosyni Kokiopoulou, July 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Ranking Recovery under Privacy Considerations

  Minoh Jeong, Alex Dytso, Martina Cardone, July 2022
  [openreview] [pdf] [bib]

• Learning the Transformer Kernel

  Sankalan Pal Chowdhury, Adamos Solomou, Kumar Avinava Dubey, Mrinmaya Sachan, July 2022
  [openreview] [pdf] [bib] [code]

• Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks

  David Alvarez-Melis, Yair Schiff, Youssef Mroueh, July 2022
  [openreview] [pdf] [bib] [code]

• Deformation Robust Roto-Scale-Translation Equivariant CNNs

  Liyao Gao, Guang Lin, Wei Zhu, July 2022
  [openreview] [pdf] [bib] [code]

• On the link between conscious function and general intelligence in humans and machines

  Arthur Juliani, Kai Arulkumaran, Shuntaro Sasai, Ryota Kanai, July 2022
  [openreview] [pdf] [bib]
  Certifications: Survey

• Non-Deterministic Behavior of Thompson Sampling with Linear Payoffs and How to Avoid It

  Doruk Kilitcioglu, Serdar Kadioglu, July 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Reproducibility

• Structural Learning in Artificial Neural Networks: A Neural Operator Perspective

  Kaitlin Maile, Luga Hervé, Dennis George Wilson, July 2022
  [openreview] [pdf] [bib]
  Certifications: Survey Event: AutoML 2023

• Adversarial Feature Augmentation and Normalization for Visual Recognition

  Tianlong Chen, Yu Cheng, Zhe Gan, Jianfeng Wang, Lijuan Wang, Jingjing Liu, Zhangyang Wang, July 2022
  [openreview] [pdf] [bib] [code]

• Your Policy Regularizer is Secretly an Adversary

  Rob Brekelmans, Tim Genewein, Jordi Grau-Moya, Gregoire Detetang, Markus Kunesch, Shane Legg, Pedro A Ortega, July 2022
  [openreview] [pdf] [bib]
  Certifications: Written by Expert Reviewer

• How Expressive are Transformers in Spectral Domain for Graphs?

  Anson Bastos, Abhishek Nadgeri, Kuldeep Singh, Hiroki Kanezashi, Toyotaro Suzumura, Isaiah Onando Mulang', July 2022
  [openreview] [pdf] [bib] [code]

• Robust and Data-efficient Q-learning by Composite Value-estimation

  Gabriel Kalweit, Maria Kalweit, Joschka Boedecker, July 2022
  [openreview] [pdf] [bib] [code]

• Iterative State Estimation in Non-linear Dynamical Systems Using Approximate Expectation Propagation

  Sanket Kamthe, So Takao, Shakir Mohamed, Marc Peter Deisenroth, July 2022
  [openreview] [pdf] [bib] [code]

• The Graph Cut Kernel for Ranked Data

  Michelangelo Conserva, Marc Peter Deisenroth, K S Sesh Kumar, July 2022
  [openreview] [pdf] [bib] [code]

• NoiLin: Improving adversarial training and correcting stereotype of noisy labels

  Jingfeng Zhang, Xilie Xu, Bo Han, Tongliang Liu, Lizhen Cui, Gang Niu, Masashi Sugiyama, June 2022
  [openreview] [pdf] [bib] [code]

• Multi-Agent Off-Policy TDC with Near-Optimal Sample and Communication Complexities

  Ziyi Chen, Yi Zhou, Rong-Rong Chen, June 2022
  [openreview] [pdf] [bib] [code]

• Benchmarking and Analyzing Unsupervised Network Representation Learning and the Illusion of Progress

  Saket Gurukar, Priyesh Vijayan, srinivasan parthasarathy, Balaraman Ravindran, Aakash Srinivasan, Goonmeet Bajaj, Chen Cai, Moniba Keymanesh, Saravana Kumar, Pranav Maneriker, Anasua Mitra, Vedang Patel, June 2022
  [openreview] [pdf] [bib] [code]

• Decoding EEG With Spiking Neural Networks on Neuromorphic Hardware

  Neelesh Kumar, Guangzhi Tang, Raymond Yoo, Konstantinos P. Michmizos, June 2022
  [openreview] [pdf] [bib] [code]

• Understanding Linearity of Cross-Lingual Word Embedding Mappings

  Xutan Peng, Mark Stevenson, Chenghua Lin, Chen Li, June 2022
  [openreview] [pdf] [bib] [code]

• TLDR: Twin Learning for Dimensionality Reduction

  Yannis Kalantidis, Carlos Eduardo Rosar Kos Lassance, Jon Almazán, Diane Larlus, June 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Clustering units in neural networks: upstream vs downstream information

  Richard D Lange, David Rolnick, Konrad Kording, June 2022
  [openreview] [pdf] [bib] [code]

• Boosting Search Engines with Interactive Agents

  Leonard Adolphs, Benjamin Börschinger, Christian Buck, Michelle Chen Huebscher, Massimiliano Ciaramita, Lasse Espeholt, Thomas Hofmann, Yannic Kilcher, Sascha Rothe, Pier Giuseppe Sessa, Lierni Sestorain, June 2022
  [openreview] [pdf] [bib] [code]

• Queried Unlabeled Data Improves and Robustifies Class-Incremental Learning

  Tianlong Chen, Sijia Liu, Shiyu Chang, Lisa Amini, Zhangyang Wang, June 2022
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• Greedy Bayesian Posterior Approximation with Deep Ensembles

  Aleksei Tiulpin, Matthew B. Blaschko, June 2022
  [openreview] [pdf] [bib] [code]

• Auto-Lambda: Disentangling Dynamic Task Relationships

  Shikun Liu, Stephen James, Andrew Davison, Edward Johns, June 2022
  [openreview] [pdf] [bib] [code]

• How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers

  Andreas Peter Steiner, Alexander Kolesnikov, Xiaohua Zhai, Ross Wightman, Jakob Uszkoreit, Lucas Beyer, May 2022
  [openreview] [pdf] [bib] [code]

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