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Reposted by arXiv math.ST Statistics Theory
Vilas Winstein: Wasserstein distances between ERGMs and Erd\H{o}s-R\'enyi models https://arxiv.org/abs/2601.14170 https://arxiv.org/pdf/2601.14170 https://arxiv.org/html/2601.14170
January 21, 2026 at 6:40 AM
Vilas Winstein: Wasserstein distances between ERGMs and Erd\H{o}s-R\'enyi models https://arxiv.org/abs/2601.14170 https://arxiv.org/pdf/2601.14170 https://arxiv.org/html/2601.14170
Reposted by arXiv math.ST Statistics Theory
Sang Yang, Zhixin Peng: Additive-Functional Approach to Transport in Periodic and Tilted Periodic Potentials https://arxiv.org/abs/2601.13561 https://arxiv.org/pdf/2601.13561 https://arxiv.org/html/2601.13561
January 21, 2026 at 6:43 AM
Sang Yang, Zhixin Peng: Additive-Functional Approach to Transport in Periodic and Tilted Periodic Potentials https://arxiv.org/abs/2601.13561 https://arxiv.org/pdf/2601.13561 https://arxiv.org/html/2601.13561
Reposted by arXiv math.ST Statistics Theory
Deep Ghoshal, Xiaofeng Shao: Resampling-free Inference for Time Series via RKHS Embedding https://arxiv.org/abs/2601.13468 https://arxiv.org/pdf/2601.13468 https://arxiv.org/html/2601.13468
January 21, 2026 at 6:54 AM
Deep Ghoshal, Xiaofeng Shao: Resampling-free Inference for Time Series via RKHS Embedding https://arxiv.org/abs/2601.13468 https://arxiv.org/pdf/2601.13468 https://arxiv.org/html/2601.13468
Reposted by arXiv math.ST Statistics Theory
Zihan Dong, Ruijia Wu, Linjun Zhang: Labels or Preferences? Budget-Constrained Learning with Human Judgments over AI-Generated Outputs https://arxiv.org/abs/2601.13458 https://arxiv.org/pdf/2601.13458 https://arxiv.org/html/2601.13458
January 21, 2026 at 6:54 AM
Zihan Dong, Ruijia Wu, Linjun Zhang: Labels or Preferences? Budget-Constrained Learning with Human Judgments over AI-Generated Outputs https://arxiv.org/abs/2601.13458 https://arxiv.org/pdf/2601.13458 https://arxiv.org/html/2601.13458
Reposted by arXiv math.ST Statistics Theory
Szabolcs Szentp\'eteri, Bal\'azs Csan\'ad Cs\'aji: Distribution-Free Confidence Ellipsoids for Ridge Regression with PAC Bounds https://arxiv.org/abs/2601.13436 https://arxiv.org/pdf/2601.13436 https://arxiv.org/html/2601.13436
January 21, 2026 at 6:54 AM
Szabolcs Szentp\'eteri, Bal\'azs Csan\'ad Cs\'aji: Distribution-Free Confidence Ellipsoids for Ridge Regression with PAC Bounds https://arxiv.org/abs/2601.13436 https://arxiv.org/pdf/2601.13436 https://arxiv.org/html/2601.13436
Reposted by arXiv math.ST Statistics Theory
Xinyuan Chen, Fan Li: Optimal estimation of generalized causal effects in cluster-randomized trials with multiple outcomes https://arxiv.org/abs/2601.13428 https://arxiv.org/pdf/2601.13428 https://arxiv.org/html/2601.13428
January 21, 2026 at 6:53 AM
Xinyuan Chen, Fan Li: Optimal estimation of generalized causal effects in cluster-randomized trials with multiple outcomes https://arxiv.org/abs/2601.13428 https://arxiv.org/pdf/2601.13428 https://arxiv.org/html/2601.13428
Reposted by arXiv math.ST Statistics Theory
Aryeh Keating, Mirjeta Pasha: A Scalable Sequential Framework for Dynamic Inverse Problems via Model Parameter Estimation https://arxiv.org/abs/2601.13347 https://arxiv.org/pdf/2601.13347 https://arxiv.org/html/2601.13347
January 21, 2026 at 6:39 AM
Aryeh Keating, Mirjeta Pasha: A Scalable Sequential Framework for Dynamic Inverse Problems via Model Parameter Estimation https://arxiv.org/abs/2601.13347 https://arxiv.org/pdf/2601.13347 https://arxiv.org/html/2601.13347
Reposted by arXiv math.ST Statistics Theory
Francesco Pedrotti: Entropy-Wasserstein regularization, defective local concentration and a cutoff criterion beyond non-negative curvature https://arxiv.org/abs/2601.13259 https://arxiv.org/pdf/2601.13259 https://arxiv.org/html/2601.13259
January 21, 2026 at 6:40 AM
Francesco Pedrotti: Entropy-Wasserstein regularization, defective local concentration and a cutoff criterion beyond non-negative curvature https://arxiv.org/abs/2601.13259 https://arxiv.org/pdf/2601.13259 https://arxiv.org/html/2601.13259
Reposted by arXiv math.ST Statistics Theory
Davidson Lova Razafindrakoto, Alain Celisse, J\'er\^ome Lacaille: Approximate full conformal prediction in RKHS https://arxiv.org/abs/2601.13102 https://arxiv.org/pdf/2601.13102 https://arxiv.org/html/2601.13102
January 21, 2026 at 6:53 AM
Davidson Lova Razafindrakoto, Alain Celisse, J\'er\^ome Lacaille: Approximate full conformal prediction in RKHS https://arxiv.org/abs/2601.13102 https://arxiv.org/pdf/2601.13102 https://arxiv.org/html/2601.13102
Reposted by arXiv math.ST Statistics Theory
Bruno Ferman, Davi Siqueira, Vitor Possebom: Partial Identification under Stratified Randomization https://arxiv.org/abs/2601.12566 https://arxiv.org/pdf/2601.12566 https://arxiv.org/html/2601.12566
January 21, 2026 at 6:35 AM
Bruno Ferman, Davi Siqueira, Vitor Possebom: Partial Identification under Stratified Randomization https://arxiv.org/abs/2601.12566 https://arxiv.org/pdf/2601.12566 https://arxiv.org/html/2601.12566
Reposted by arXiv math.ST Statistics Theory
Tingxuan Han, Yuhao Wang: Rerandomization for quantile treatment effects https://arxiv.org/abs/2601.12540 https://arxiv.org/pdf/2601.12540 https://arxiv.org/html/2601.12540
January 21, 2026 at 6:53 AM
Tingxuan Han, Yuhao Wang: Rerandomization for quantile treatment effects https://arxiv.org/abs/2601.12540 https://arxiv.org/pdf/2601.12540 https://arxiv.org/html/2601.12540
Reposted by arXiv math.ST Statistics Theory
Junyu Cao, Ruijiang Gao, Esmaeil Keyvanshokooh, Jianhao Ma: LIBRA: Language Model Informed Bandit Recourse Algorithm for Personalized Treatment Planning https://arxiv.org/abs/2601.11905 https://arxiv.org/pdf/2601.11905 https://arxiv.org/html/2601.11905
January 21, 2026 at 6:29 AM
Junyu Cao, Ruijiang Gao, Esmaeil Keyvanshokooh, Jianhao Ma: LIBRA: Language Model Informed Bandit Recourse Algorithm for Personalized Treatment Planning https://arxiv.org/abs/2601.11905 https://arxiv.org/pdf/2601.11905 https://arxiv.org/html/2601.11905
Reposted by arXiv math.ST Statistics Theory
Ricardo J. Sandoval, Sivaraman Balakrishnan, Avi Feller, Michael I. Jordan, Ian Waudby-Smith: On Nonasymptotic Confidence Intervals for Treatment Effects in Randomized Experiments https://arxiv.org/abs/2601.11744 https://arxiv.org/pdf/2601.11744 https://arxiv.org/html/2601.11744
January 21, 2026 at 6:53 AM
Ricardo J. Sandoval, Sivaraman Balakrishnan, Avi Feller, Michael I. Jordan, Ian Waudby-Smith: On Nonasymptotic Confidence Intervals for Treatment Effects in Randomized Experiments https://arxiv.org/abs/2601.11744 https://arxiv.org/pdf/2601.11744 https://arxiv.org/html/2601.11744
Reposted by arXiv math.ST Statistics Theory
Bergna, Depeweg, Ordonez, Plenk, Cartea, Hernandez-Lobato: Post-Hoc Uncertainty Quantification in Pre-Trained Neural Networks via Activation-Level Gaussian Processes https://arxiv.org/abs/2502.20966 https://arxiv.org/pdf/2502.20966 https://arxiv.org/html/2502.20966
March 3, 2025 at 6:18 AM
Bergna, Depeweg, Ordonez, Plenk, Cartea, Hernandez-Lobato: Post-Hoc Uncertainty Quantification in Pre-Trained Neural Networks via Activation-Level Gaussian Processes https://arxiv.org/abs/2502.20966 https://arxiv.org/pdf/2502.20966 https://arxiv.org/html/2502.20966
Annika Betken, Giorgio Micali, Manuel Ruiz Mar\'in: Symmetry Testing in Time Series using Ordinal Patterns: A U-Statistic Approach https://arxiv.org/abs/2601.14223 https://arxiv.org/pdf/2601.14223 https://arxiv.org/html/2601.14223
January 21, 2026 at 6:41 AM
Annika Betken, Giorgio Micali, Manuel Ruiz Mar\'in: Symmetry Testing in Time Series using Ordinal Patterns: A U-Statistic Approach https://arxiv.org/abs/2601.14223 https://arxiv.org/pdf/2601.14223 https://arxiv.org/html/2601.14223
Anders Bredahl Kock, David Preinerstorfer: Robustness for free: asymptotic size and power of max-tests in high dimensions https://arxiv.org/abs/2601.14013 https://arxiv.org/pdf/2601.14013 https://arxiv.org/html/2601.14013
January 21, 2026 at 6:41 AM
Anders Bredahl Kock, David Preinerstorfer: Robustness for free: asymptotic size and power of max-tests in high dimensions https://arxiv.org/abs/2601.14013 https://arxiv.org/pdf/2601.14013 https://arxiv.org/html/2601.14013
Dong Huang, Pengkun Yang: Information-Theoretic and Computational Limits of Correlation Detection under Graph Sampling https://arxiv.org/abs/2601.13966 https://arxiv.org/pdf/2601.13966 https://arxiv.org/html/2601.13966
January 21, 2026 at 6:41 AM
Dong Huang, Pengkun Yang: Information-Theoretic and Computational Limits of Correlation Detection under Graph Sampling https://arxiv.org/abs/2601.13966 https://arxiv.org/pdf/2601.13966 https://arxiv.org/html/2601.13966
Akira Shinkyu: Uniform Consistency of Generalized Cross-Validation for Ridge Regression in High-Dimensional Misspecified Linear Models https://arxiv.org/abs/2601.13955 https://arxiv.org/pdf/2601.13955 https://arxiv.org/html/2601.13955
January 21, 2026 at 6:41 AM
Akira Shinkyu: Uniform Consistency of Generalized Cross-Validation for Ridge Regression in High-Dimensional Misspecified Linear Models https://arxiv.org/abs/2601.13955 https://arxiv.org/pdf/2601.13955 https://arxiv.org/html/2601.13955
Philip Boeken, Eduardo Skapinakis, Konstantin Genin, Joris M. Mooij: Topological Criteria for Hypothesis Testing with Finite-Precision Measurements https://arxiv.org/abs/2601.13946 https://arxiv.org/pdf/2601.13946 https://arxiv.org/html/2601.13946
January 21, 2026 at 6:41 AM
Philip Boeken, Eduardo Skapinakis, Konstantin Genin, Joris M. Mooij: Topological Criteria for Hypothesis Testing with Finite-Precision Measurements https://arxiv.org/abs/2601.13946 https://arxiv.org/pdf/2601.13946 https://arxiv.org/html/2601.13946
Kohei Kawamoto, Yuichi Goto, Koji Tsukuda: On spectral clustering under non-isotropic Gaussian mixture models https://arxiv.org/abs/2601.13930 https://arxiv.org/pdf/2601.13930 https://arxiv.org/html/2601.13930
January 21, 2026 at 6:41 AM
Kohei Kawamoto, Yuichi Goto, Koji Tsukuda: On spectral clustering under non-isotropic Gaussian mixture models https://arxiv.org/abs/2601.13930 https://arxiv.org/pdf/2601.13930 https://arxiv.org/html/2601.13930
Shir Tapiro-Moshe, Yariv Aizenbud, Barak Sober: Moving Least Squares without Quasi-Uniformity: A Stochastic Approach https://arxiv.org/abs/2601.13782 https://arxiv.org/pdf/2601.13782 https://arxiv.org/html/2601.13782
January 21, 2026 at 6:41 AM
Shir Tapiro-Moshe, Yariv Aizenbud, Barak Sober: Moving Least Squares without Quasi-Uniformity: A Stochastic Approach https://arxiv.org/abs/2601.13782 https://arxiv.org/pdf/2601.13782 https://arxiv.org/html/2601.13782
G\'erard Biau (SU, IUF, MEGAVOLT), Claire Boyer (IUF, CELESTE): A Note on k-NN Gating in RAG https://arxiv.org/abs/2601.13744 https://arxiv.org/pdf/2601.13744 https://arxiv.org/html/2601.13744
January 21, 2026 at 6:41 AM
G\'erard Biau (SU, IUF, MEGAVOLT), Claire Boyer (IUF, CELESTE): A Note on k-NN Gating in RAG https://arxiv.org/abs/2601.13744 https://arxiv.org/pdf/2601.13744 https://arxiv.org/html/2601.13744
Dimitri Konen: Inverting the Fisher information operator in non-linear models https://arxiv.org/abs/2601.13254 https://arxiv.org/pdf/2601.13254 https://arxiv.org/html/2601.13254
January 21, 2026 at 6:41 AM
Dimitri Konen: Inverting the Fisher information operator in non-linear models https://arxiv.org/abs/2601.13254 https://arxiv.org/pdf/2601.13254 https://arxiv.org/html/2601.13254
Hanne Kekkonen, Andreas Tataris: Random tree Besov priors: Data-driven regularisation parameter selection https://arxiv.org/abs/2601.12957 https://arxiv.org/pdf/2601.12957 https://arxiv.org/html/2601.12957
January 21, 2026 at 6:41 AM
Hanne Kekkonen, Andreas Tataris: Random tree Besov priors: Data-driven regularisation parameter selection https://arxiv.org/abs/2601.12957 https://arxiv.org/pdf/2601.12957 https://arxiv.org/html/2601.12957
Nadezhda Gribkova, Jianxi Su, Mengqi Wang: Expansion and Bounds for the Bias of Empirical Tail Value-at-Risk https://arxiv.org/abs/2601.12064 https://arxiv.org/pdf/2601.12064 https://arxiv.org/html/2601.12064
January 21, 2026 at 6:41 AM
Nadezhda Gribkova, Jianxi Su, Mengqi Wang: Expansion and Bounds for the Bias of Empirical Tail Value-at-Risk https://arxiv.org/abs/2601.12064 https://arxiv.org/pdf/2601.12064 https://arxiv.org/html/2601.12064