Journal Statistics

186
Journal of the Royal Statistical Society Series B
papers tracked
410
Journal of the American Statistical Association
papers tracked
162
Annals of Statistics
papers tracked
120
Biometrika
papers tracked
406
Journal of Machine Learning Research
papers tracked

Recent Papers

JMLR Jul 06, 2026
High-Dimensional Analysis of Gradient Flow for Extensive-Width Quadratic Neural Networks

Francis Bach, Simon Martin, Giulio Biroli

Machine Learning High-Dimensional Statistics
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JMLR Jul 06, 2026
Error Analyses of Auto-Regressive Video Diffusion Models

Zhuoran Yang, Jing Wang, Fengzhuo Zhang et al.

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JMLR Jul 06, 2026
Near-optimal Delta-convex Estimation of Lipschitz Functions

G{\'{a}}bor Bal{\'{a}}zs

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JMLR Jul 06, 2026
The Sample Complexity of Parameter-Free Stochastic Convex Optimization

Jared Lawrence, Ari Kalinsky, Hannah Bradfield et al.

Computational Statistics
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JMLR Jul 06, 2026
End-to-End Deep Learning for Predicting Metric Space-Valued Outputs

Su I Iao, Yidong Zhou, Hans-Georg M{\"{u}}ller

Machine Learning
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JMLR Jul 06, 2026
Graph-based Clustering Revisited: A Relaxation of Kernel k-Means Perspective

Wenlong Lyu, Yuheng Jia, Hui Liu et al.

Nonparametric Statistics
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JMLR Jul 06, 2026
Learning to Play Two-Player Perfect-Information Games without Knowledge

Quentin Cohen-Solal

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JMLR Jul 06, 2026
Doubly Debiased Robust Subsampling for Transfer Learning

Tao Wang, Weng Kee Wong

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JMLR Jul 06, 2026
Abstract Gradient Training: A Unified Certification Framework for Data Poisoning, Unlearning, and Differential Privacy

Philip Sosnin, Matthew Wicker, Josh Collyer et al.

Machine Learning
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JMLR Jul 06, 2026
Mixing times of data-augmentation Gibbs samplers for high-dimensional probit regression

Giacomo Zanella, Filippo Ascolani

Machine Learning High-Dimensional Statistics
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JMLR Jul 06, 2026
Underdamped Langevin MCMC with third order convergence

Maximilian Scott, D{\'{a}}ire O'Kane, Andraž Jelinčič et al.

Bayesian Statistics
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JMLR Jul 06, 2026
Approximation-Free Differentiable Oblique Decision Trees

Subrat Prasad Panda, Blaise Genest, Arvind Easwaran

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JMLR Jul 06, 2026
Minimax Optimal Convergence of Gradient Descent in Logistic Regression via Large and Adaptive Stepsizes

Peter L. Bartlett, Ruiqi Zhang, Jingfeng Wu et al.

Machine Learning
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JMLR Jul 06, 2026
Adaptive Nonparametric Perturbations of Parametric Models with Generalized Bayes

Bohan Wu, Yixin Wang, Eli N. Weinstein et al.

Nonparametric Statistics Bayesian Statistics
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JMLR Jul 06, 2026
Robust training of implicit generative models for multivariate and heavy-tailed distributions with an invariant statistical loss

Jos{\'{e}} Manuel de Frutos, Manuel A. V{\'{a}}zquez, Pablo M. Olmos et al.

Machine Learning
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JMLR Jul 06, 2026
Gradient Span Algorithms Make Predictable Progress in High Dimension

Felix Benning, Leif D{\"{o}}ring

Computational Statistics
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JMLR Jul 06, 2026
py/cuTAGI: An Open-Source Library for Tractable Approximate Gaussian Inference in Bayesian Neural Networks

Luong-Ha Nguyen, James-A. Goulet, Miquel Florensa-Montilla et al.

Machine Learning Bayesian Statistics
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JMLR Jul 06, 2026
Statistical Test for Attention in Transformers for Images and Time Series

Tomohiro Shiraishi, Daiki Miwa, Teruyuki Katsuoka et al.

Time Series
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JMLR Jul 06, 2026
Accelerating Constrained Sampling: A Large Deviations Approach

Lingjiong Zhu, Yingli Wang, Changwei Tu et al.

Machine Learning
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JMLR Jul 06, 2026
Learning general conditional independence structures via the neighbourhood lattice

Bryon Aragam, Arash A. Amini, Qing Zhou

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