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Journal of Machine Learning Research (JMLR)

Proceedings of Machine Learning Research (PMLR)

Data-centric Machine Learning Research (DMLR)

Accepted papers

• 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]

• 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

  Yae Jee Cho, Divyansh Jhunjhunwala, Tian Li, Virginia Smith, Gauri Joshi, March 2024
  [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

  Akshaj Kumar Veldanda, Ivan Brugere, Sanghamitra Dutta, Alan Mishler, Siddharth Garg, March 2024
  [openreview] [pdf] [bib]

• E(n)-equivariant Graph Neural Cellular Automata

  Gennaro Gala, Daniele Grattarola, Erik Quaeghebeur, March 2024
  [openreview] [pdf] [bib] [code]

• Layer-diverse Negative Sampling for Graph Neural Networks

  Wei Duan, Jie Lu, Yu Guang Wang, Junyu Xuan, March 2024
  [openreview] [pdf] [bib]

• Personalized Federated Learning with Spurious Features: An Adversarial Approach

  Xiaoyang Wang, Han Zhao, Klara Nahrstedt, Sanmi Koyejo, March 2024
  [openreview] [pdf] [bib]

• Improving and generalizing flow-based generative models with minibatch optimal transport

  Alexander Tong, Kilian FATRAS, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Guy Wolf, Yoshua Bengio, March 2024
  [openreview] [pdf] [bib]
  Certifications: Written by Expert Reviewer

• A Pseudo-Metric between Probability Distributions based on Depth-Trimmed Regions

  Guillaume Staerman, Pavlo Mozharovskyi, Pierre Colombo, Stephan Clémençon, Florence d'Alché-Buc, March 2024
  [openreview] [pdf] [bib] [code]

• World Models via Policy-Guided Trajectory Diffusion

  Marc Rigter, Jun Yamada, Ingmar Posner, March 2024
  [openreview] [pdf] [bib] [code]

• Adapting Contrastive Language-Image Pretrained (CLIP) Models for Out-of-Distribution Detection

  Nikolas Adaloglou, Felix Michels, Tim Kaiser, Markus Kollmann, March 2024
  [openreview] [pdf] [bib] [code]

• Multi-conditioned Graph Diffusion for Neural Architecture Search

  Rohan Asthana, Joschua Conrad, Youssef Dawoud, Maurits Ortmanns, Vasileios Belagiannis, March 2024
  [openreview] [pdf] [bib] [code]

• How does over-squashing affect the power of GNNs?

  Francesco Di Giovanni, T. Konstantin Rusch, Michael Bronstein, Andreea Deac, Marc Lackenby, Siddhartha Mishra, Petar Veličković, March 2024
  [openreview] [pdf] [bib]

• AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks

  Alexander Tornede, Difan Deng, Theresa Eimer, Joseph Giovanelli, Aditya Mohan, Tim Ruhkopf, Sarah Segel, Daphne Theodorakopoulos, Tanja Tornede, Henning Wachsmuth, Marius Lindauer, March 2024
  [openreview] [pdf] [bib]

• Exposing and Addressing Cross-Task Inconsistency in Unified Vision-Language Models

  Adyasha Maharana, Amita Kamath, Christopher Clark, Mohit Bansal, Aniruddha Kembhavi, March 2024
  [openreview] [pdf] [bib]

• Controlling the Inductive Bias of Wide Neural Networks by Modifying the Kernel’s Spectrum

  Amnon Geifman, Daniel Barzilai, Ronen Basri, Meirav Galun, March 2024
  [openreview] [pdf] [bib]

• Attending to Graph Transformers

  Luis Müller, Mikhail Galkin, Christopher Morris, Ladislav Rampášek, March 2024
  [openreview] [pdf] [bib] [code]

• Discovering Model Structure of Dynamical Systems with Combinatorial Bayesian Optimization

  Lucas Rath, Alexander von Rohr, Andreas Schultze, Sebastian Trimpe, Burkhard Corves, March 2024
  [openreview] [pdf] [bib] [code]

• LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Models

  Long Lian, Boyi Li, Adam Yala, Trevor Darrell, March 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Featured

• An Improved Federated Clustering Algorithm with Model-based Clustering

  Harsh Vardhan, Avishek Ghosh, Arya Mazumdar, March 2024
  [openreview] [pdf] [bib] [code]

• Series of Hessian-Vector Products for Tractable Saddle-Free Newton Optimisation of Neural Networks

  Elre Talea Oldewage, Ross M Clarke, José Miguel Hernández-Lobato, March 2024
  [openreview] [pdf] [bib] [code]

• Demographically-Informed Prediction Discrepancy Index: Early Warnings of Demographic Biases for Unlabeled Populations

  Lucas Mansilla, Estanislao Claucich, Rodrigo Echeveste, Diego H Milone, Enzo Ferrante, March 2024
  [openreview] [pdf] [bib] [code]

• Fast Training of Diffusion Models with Masked Transformers

  Hongkai Zheng, Weili Nie, Arash Vahdat, Anima Anandkumar, March 2024
  [openreview] [pdf] [bib] [code]

• Functional Linear Regression of Cumulative Distribution Functions

  Qian Zhang, Anuran Makur, Kamyar Azizzadenesheli, March 2024
  [openreview] [pdf] [bib]

• Bias/Variance is not the same as Approximation/Estimation

  Gavin Brown, Riccardo Ali, March 2024
  [openreview] [pdf] [bib] [code]

• Incorporating Prior Knowledge into Neural Networks through an Implicit Composite Kernel

  Ziyang Jiang, Tongshu Zheng, Yiling Liu, David Carlson, March 2024
  [openreview] [pdf] [bib] [code]

• Using Sum-Product Networks to Assess Uncertainty in Deep Active Learning

  Mohamadsadegh Khosravani, Sandra Zilles, March 2024
  [openreview] [pdf] [bib]

• How Much Pre-training Is Enough to Discover a Good Subnetwork?

  Cameron R. Wolfe, Fangshuo Liao, Qihan Wang, Junhyung Lyle Kim, Anastasios Kyrillidis, March 2024
  [openreview] [pdf] [bib]

• Pull-back Geometry of Persistent Homology Encodings

  Shuang Liang, Renata Turkes, Jiayi Li, Nina Otter, Guido Montufar, March 2024
  [openreview] [pdf] [bib] [code]

• MC Layer Normalization for calibrated uncertainty in Deep Learning

  Thomas Frick, Diego Antognini, Ioana Giurgiu, Benjamin F Grewe, Cristiano Malossi, Rong J.B. Zhu, Mattia Rigotti, March 2024
  [openreview] [pdf] [bib] [code]

• Kernel Normalized Convolutional Networks

  Reza Nasirigerdeh, Reihaneh Torkzadehmahani, Daniel Rueckert, Georgios Kaissis, March 2024
  [openreview] [pdf] [bib] [code]

• A VAE-based Framework for Learning Multi-Level Neural Granger-Causal Connectivity

  Jiahe Lin, Huitian Lei, George Michailidis, March 2024
  [openreview] [pdf] [bib] [code]

• Exploit CAM by itself: Complementary Learning System for Weakly Supervised Semantic Segmentation

  Wankou Yang, Jiren Mai, Fei Zhang, Tongliang Liu, Bo Han, March 2024
  [openreview] [pdf] [bib] [code]

• Learning from Natural Language Feedback

  Angelica Chen, Jérémy Scheurer, Jon Ander Campos, Tomasz Korbak, Jun Shern Chan, Samuel R. Bowman, Kyunghyun Cho, Ethan Perez, March 2024
  [openreview] [pdf] [bib] [code]

• Manifold Contrastive Learning with Variational Lie Group Operators

  Kion Fallah, Alec Helbling, Kyle A. Johnsen, Christopher John Rozell, February 2024
  [openreview] [pdf] [bib] [code]

• Pseudo-Differential Neural Operator: Generalize Fourier Neural operator for Learning Solution Operators of Partial Differential Equations

  Jin Young Shin, Jae Yong Lee, Hyung Ju Hwang, February 2024
  [openreview] [pdf] [bib]

• Are Population Graphs Really as Powerful as Believed?

  Tamara T. Müller, Sophie Starck, Kyriaki-Margarita Bintsi, Alexander Ziller, Rickmer Braren, Georgios Kaissis, Daniel Rueckert, February 2024
  [openreview] [pdf] [bib] [code]

• Multitask Learning Can Improve Worst-Group Outcomes

  Atharva Kulkarni, Lucio M. Dery, Amrith Setlur, Aditi Raghunathan, Ameet Talwalkar, Graham Neubig, February 2024
  [openreview] [pdf] [bib] [code]

• ASPEST: Bridging the Gap Between Active Learning and Selective Prediction

  Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan O Arik, Somesh Jha, Tomas Pfister, February 2024
  [openreview] [pdf] [bib] [code]

• Statistical Component Separation for Targeted Signal Recovery in Noisy Mixtures

  Bruno Régaldo-Saint Blancard, Michael Eickenberg, February 2024
  [openreview] [pdf] [bib] [code]

• A density estimation perspective on learning from pairwise human preferences

  Vincent Dumoulin, Daniel D. Johnson, Pablo Samuel Castro, Hugo Larochelle, Yann Dauphin, February 2024
  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Budgeted Online Model Selection and Fine-Tuning via Federated Learning

  Pouya M. Ghari, Yanning Shen, February 2024
  [openreview] [pdf] [bib] [code]

• ModuLoRA: Finetuning 2-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers

  Junjie Yin, Jiahao Dong, Yingheng Wang, Christopher De Sa, Volodymyr Kuleshov, February 2024
  [openreview] [pdf] [bib]
  Certifications: Featured

• 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

  Linus Aronsson, Morteza Haghir Chehreghani, February 2024
  [openreview] [pdf] [bib] [code]

• Effective Latent Differential Equation Models via Attention and Multiple Shooting

  Germán Abrevaya, Mahta Ramezanian-Panahi, Jean-Christophe Gagnon-Audet, Pablo Polosecki, Irina Rish, Silvina Ponce Dawson, Guillermo Cecchi, Guillaume Dumas, February 2024
  [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]

• Why should autoencoders work?

  Matthew Kvalheim, Eduardo Sontag, February 2024
  [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

• Expected Pinball Loss For Quantile Regression And Inverse CDF Estimation

  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

  Satoshi Hayakawa, Tetsuro Morimura, February 2024
  [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]

• 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]

• 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

• 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

• 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

• 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

• 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]

• 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]

• 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]

• 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

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  [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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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 William 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

• 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

• 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

• 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

• 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 S. 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

• 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

• 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]

• 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

• 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

• 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

• 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]

• 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

• 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

• 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

• 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

• 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]

• 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

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  [openreview] [pdf] [bib]

• No More Pesky Hyperparameters: Offline Hyperparameter Tuning for RL

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  [openreview] [pdf] [bib]

• Mean-Field Langevin Dynamics : Exponential Convergence and Annealing

  Lénaïc Chizat, August 2022
  [openreview] [pdf] [bib] [code]

• Variational Disentanglement for Domain Generalization

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  [openreview] [pdf] [bib]

• On Robustness to Missing Video for Audiovisual Speech Recognition

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  [openreview] [pdf] [bib]

• Identifying Causal Structure in Dynamical Systems

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  [openreview] [pdf] [bib] [code]

• Understanding AdamW through Proximal Methods and Scale-Freeness

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  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Diagnosing and Fixing Manifold Overfitting in Deep Generative Models

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  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Do ReLU Networks Have An Edge When Approximating Compactly-Supported Functions?

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  [openreview] [pdf] [bib]

• Recurrent networks, hidden states and beliefs in partially observable environments

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  [openreview] [pdf] [bib]

• Self-supervise, Refine, Repeat: Improving Unsupervised Anomaly Detection

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  [openreview] [pdf] [bib]

• A Comprehensive Study of Real-Time Object Detection Networks Across Multiple Domains: A Survey

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  [openreview] [pdf] [bib]
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• Domain-invariant Feature Exploration for Domain Generalization

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  [openreview] [pdf] [bib] [code]

• Stable and Interpretable Unrolled Dictionary Learning

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  [openreview] [pdf] [bib] [code]

• Exploring Generative Neural Temporal Point Process

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  [openreview] [pdf] [bib] [code]

• Improving the Trainability of Deep Neural Networks through Layerwise Batch-Entropy Regularization

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  [openreview] [pdf] [bib] [code]

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  [openreview] [pdf] [bib]

• Max-Affine Spline Insights Into Deep Network Pruning

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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]

• Learning to Switch Among Agents in a Team via 2-Layer Markov Decision Processes

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  [openreview] [pdf] [bib] [code]

• A Self-Supervised Framework for Function Learning and Extrapolation

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  [openreview] [pdf] [bib] [code]

• Deep Classifiers with Label Noise Modeling and Distance Awareness

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  [openreview] [pdf] [bib] [code]
  Certifications: Written by Expert Reviewer

• Ranking Recovery under Privacy Considerations

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  [openreview] [pdf] [bib]

• Learning the Transformer Kernel

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  [openreview] [pdf] [bib] [code]

• Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks

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  [openreview] [pdf] [bib] [code]

• Deformation Robust Roto-Scale-Translation Equivariant CNNs

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  [openreview] [pdf] [bib] [code]

• On the link between conscious function and general intelligence in humans and machines

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  [openreview] [pdf] [bib]
  Certifications: Survey

• Non-Deterministic Behavior of Thompson Sampling with Linear Payoffs and How to Avoid It

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  [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

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  [openreview] [pdf] [bib] [code]

• Your Policy Regularizer is Secretly an Adversary

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  [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

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  [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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