JMLR Volume 27

• The surrogate Gibbs-posterior of a corrected stochastic MALA: Towards uncertainty quantification for neural networks

  Sebastian Bieringer, Gregor Kasieczka, Maximilian F. Steffen, Mathias Trabs (1):1−50, 2026 codePDF BibTeX

• Online Detection of Changes in Moment--Based Projections: When to Retrain Deep Learners or Update Portfolios?

  Ansgar Steland (2):1−50, 2026 PDF BibTeX

• Efficient frequent directions algorithms for approximate decomposition of matrices and higher-order tensors

  Maolin Che, Yimin Wei, Hong Yan (3):1−56, 2026 PDF BibTeX

• Identifying Weight-Variant Latent Causal Models

  Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi (4):1−49, 2026 codePDF BibTeX

• Classification Under Local Differential Privacy with Model Reversal and Model Averaging

  Caihong Qin, Yang Bai (5):1−44, 2026 PDF BibTeX

• Stochastic Gradient Methods: Bias, Stability and Generalization

  Shuang Zeng, Yunwen Lei (6):1−55, 2026 PDF BibTeX

• Extending Mean-Field Variational Inference via Entropic Regularization: Theory and Computation

  Bohan Wu, David M. Blei (7):1−68, 2026 PDF BibTeX

• skwdro: a library for Wasserstein distributionally robust machine learning

  Vincent Florian, Waïss Azizian, Franck Iutzeler, Jérôme Malick (8):1−7, 2026 codePDF BibTeX

• Guaranteed Nonconvex Low-Rank Tensor Estimation via Scaled Gradient Descent

  Tong Wu (9):1−90, 2026 codePDF BibTeX

• A Data-Augmented Contrastive Learning Approach to Nonparametric Density Estimation

  Chenghao Li, Yuanyuan Lin (10):1−47, 2026 codePDF BibTeX

• Nonlocal Techniques for the Analysis of Deep ReLU Neural Network Approximations

  Cornelia Schneider, Mario Ullrich, Jan Vybíral (11):1−41, 2026 PDF BibTeX

• Nonlinear function-on-function regression by RKHS

  Peijun Sang, Bing Li (12):1−54, 2026 PDF BibTeX

• UQLM: A Python Package for Uncertainty Quantification in Large Language Models

  Dylan Bouchard, Mohit Singh Chauhan, David Skarbrevik, Ho-Kyeong Ra, Viren Bajaj, Zeya Ahmad (13):1−10, 2026 codePDF BibTeX

• A Reinforcement Learning Approach in Multi-Phase Second-Price Auction Design

  Rui Ai, Boxiang Lyu, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan (14):1−55, 2026 codePDF BibTeX

• Error Analysis for Deep ReLU Feedforward Density-Ratio Estimation with Bregman Divergence

  Siming Zheng, Guohao Shen, Yuanyuan Lin, Jian Huang (15):1−60, 2026 PDF BibTeX

• Flexible Functional Treatment Effect Estimation

  Jiayi Wang, Raymond K. W. Wong, Xiaoke Zhang, Kwun Chuen Gary Chan (16):1−48, 2026 PDF BibTeX

• Neural Network Parameter-optimization of Gaussian Pre-marginalized Directed Acyclic Graphs

  Mehrzad Saremi (17):1−53, 2026 codePDF BibTeX

• Extrapolated Markov Chain Oversampling Method for Imbalanced Text Classification

  Aleksi Avela, Pauliina Ilmonen (18):1−28, 2026 codePDF BibTeX

• An Anytime Algorithm for Good Arm Identification

  Marc Jourdan, Andrée Delahaye-Duriez, Clémence Réda (19):1−90, 2026 PDF BibTeX

• Simulation-based Calibration of Uncertainty Intervals under Approximate Bayesian Estimation

  Terrance D. Savitsky, Julie Gershunskaya (20):1−32, 2026 PDF BibTeX

• Learning Bayesian Network Classifiers to Minimize Class Variable Parameters

  Shouta Sugahara, Koya Kato, James Cussens, Maomi Ueno (21):1−41, 2026 PDF BibTeX

• Nonparametric Estimation of a Factorizable Density using Diffusion Models

  Hyeok Kyu Kwon, Dongha Kim, Ilsang Ohn, Minwoo Chae (22):1−125, 2026 PDF BibTeX

• The Distribution of Ridgeless Least Squares Interpolators

  Qiyang Han, Xiaocong Xu (23):1−94, 2026 PDF BibTeX

• LazyDINO: Fast, Scalable, and Efficiently Amortized Bayesian Inversion via Structure-Exploiting and Surrogate-Driven Measure Transport

  Lianghao Cao, Joshua Chen, Michael Brennan, Thomas O'Leary-Roseberry, Youssef Marzouk, Omar Ghattas (24):1−71, 2026 codePDF BibTeX

• A Common Interface for Automatic Differentiation

  Guillaume Dalle, Adrian Hill (25):1−13, 2026 codePDF BibTeX

• Refined Risk Bounds for Unbounded Losses via Transductive Priors

  Jian Qian, Alexander Rakhlin, Nikita Zhivotovskiy (26):1−64, 2026 PDF BibTeX

• Decorrelated Local Linear Estimator: Inference for Non-linear Effects in High-dimensional Additive Models

  Zijian Guo, Wei Yuan, Cunhui Zhang (27):1−79, 2026 PDF BibTeX

• Communication-efficient Distributed Statistical Inference for Massive Data with Heterogeneous Auxiliary Information

  Miaomiao Yu, Zhongfeng Jiang, Jiaxuan Li, Yong Zhou (28):1−39, 2026 PDF BibTeX

• Generative Bayesian Inference with GANs

  Yuexi Wang, Veronika Rockova (29):1−48, 2026 PDF BibTeX

• Exploring Novel Uncertainty Quantification through Forward Intensity Function Modeling

  Yudong Wang, Zhi-Sheng Ye, Cheng Yong Tang (30):1−63, 2026 PDF BibTeX

• Persistence Diagrams Estimation of Multivariate Piecewise Hölder-continuous Signals

  Hugo Henneuse (31):1−55, 2026 PDF BibTeX

• CHANI: Correlation-based Hawkes Aggregation of Neurons with bio-Inspiration

  Sophie Jaffard, Samuel Vaiter, Patricia Reynaud-Bouret (32):1−62, 2026 codePDF BibTeX

• Finite Neural Networks as Mixtures of Gaussian Processes: From Provable Error Bounds to Prior Selection

  Steven Adams, Andrea Patanè, Morteza Lahijanian, Luca Laurenti (33):1−52, 2026 PDF BibTeX

• Optimization and Generalization of Gradient Descent for Shallow ReLU Networks with Minimal Width

  Yunwen Lei, Puyu Wang, Yiming Ying, Ding-Xuan Zhou (34):1−35, 2026 PDF BibTeX

• Adaptive Forward Stepwise: A Method for High Sparsity Regression

  Ivy Zhang, Robert Tibshirani (35):1−24, 2026 PDF BibTeX

• Optimizing Attention with Mirror Descent: Generalized Max-Margin Token Selection

  Addison Kristanto Julistiono, Davoud Ataee Tarzanagh, Navid Azizan (36):1−61, 2026 codePDF BibTeX

• Hierarchical Causal Models

  Eli N. Weinstein, David M. Blei (37):1−73, 2026 codePDF BibTeX

• Reparameterized Complex-valued Neurons Can Efficiently Learn More than Real-valued Neurons via Gradient Descent

  Jin-Hui Wu, Shao-Qun Zhang, Yuan Jiang, Zhi-Hua Zhou (38):1−51, 2026 PDF BibTeX

• Unsupervised Feature Selection via Nonnegative Orthogonal Constrained Regularized Minimization

  Yan Li, Defeng Sun, Liping Zhang (39):1−44, 2026 PDF BibTeX

• A causal fused lasso for interpretable heterogeneous treatment effects estimation

  Oscar Hernan Madrid Padilla, Yanzhen Chen, Carlos Misael Madrid Padilla, Gabriel Ruiz (40):1−56, 2026 PDF BibTeX

• Bayesian Inference of Contextual Bandit Policies via Empirical Likelihood

  Jiangrong Ouyang, Mingming Gong, Howard Bondell (41):1−28, 2026 codePDF BibTeX

• Convergence and complexity of block majorization-minimization for constrained block-Riemannian optimization

  Yuchen Li, Laura Balzano, Deanna Needell, Hanbaek Lyu (42):1−77, 2026 PDF BibTeX

• Two-way Node Popularity Model for Directed and Bipartite Networks

  Bing-Yi Jing, Ting Li, Jiangzhou Wang, Ya Wang (43):1−73, 2026 codePDF BibTeX

• A Symplectic Analysis of Alternating Mirror Descent

  Jonas E. Katona, Xiuyuan Wang, Andre Wibisono (44):1−61, 2026 codePDF BibTeX

• Contrasting Local and Global Modeling with Machine Learning and Satellite Data: A Case Study Estimating Tree Canopy Height in African Savannas

  Esther Rolf, Lucia Gordon, Milind Tambe, Andrew Davies (45):1−37, 2026 codePDF BibTeX

• Boosted Control Functions: Distribution Generalization and Invariance in Confounded Models

  Nicola Gnecco, Jonas Peters, Sebastian Engelke, Niklas Pfister (46):1−57, 2026 codePDF BibTeX

• DCatalyst: A Unified Accelerated Framework for Decentralized Optimization

  TIanyu Cao, Xiaokai Chen, Gesualdo Scutari (47):1−57, 2026 PDF BibTeX

• Covariate-dependent Hierarchical Dirichlet Processes

  Huizi Zhang, Sara Wade, Natalia Bochkina (48):1−99, 2026 PDF BibTeX

• Online Bernstein-von Mises theorem

  Jeyong Lee, Junhyeok Choi, Minwoo Chae (49):1−124, 2026 PDF BibTeX

• Transformers Can Overcome the Curse of Dimensionality: A Theoretical Study from an Approximation Perspective

  Yuling Jiao, Yanming Lai, Yang Wang, Bokai Yan (50):1−34, 2026 PDF BibTeX