Yonghan Jung, Bogyeong Kang Data-Driven Information-Theoretic Causal Bounds under Unmeasured Confounding https://arxiv.org/abs/2601.17160

Bamdad Hosseini, Ziqi Huang Error Analysis of Bayesian Inverse Problems with Generative Priors https://arxiv.org/abs/2601.17374

David L. Donoho, Jian Kang, Xihong Lin, Bhramar Mukherjee, Dan Nettleton, Rebecca Nugent, Abel Rodriguez, Eric P. Xing, Tian Zheng, Hongtu Zhu "Rebuilding" Statistics in the Age of AI: A Town Hall Discussion on Culture, Infrastructure, and Training https://arxiv.org/abs/2601.17510

Yuan Bian, Grace Y. Yi, Wenqing He Boosting methods for interval-censored data with regression and classification https://arxiv.org/abs/2601.17973

Bokan Chen, Raiden Hasegawa, Adriaan Hilbers, Ross Koningstein, Ana Radovanovi\'c, Utkarsh Shah, Gabriela Volpato, Mohamed Ahmed, Tim Cary, Rod Frowd A Cherry-Picking Approach to Large Load Shaping for More Effective Carbon Reduction https://arxiv.org/abs/2601.17990

Gemma E. Moran, Anandi Krishnan Nonlinear multi-study factor analysis https://arxiv.org/abs/2601.18128

Heguang Lin, Binhao Chen, Mengze Li, Daniel Pimentel-Alarc\'on, Matthew L. Malloy Exact Minimum-Volume Confidence Set Intersection for Multinomial Outcomes https://arxiv.org/abs/2601.18145

Yadang Alexis Rouzoumka, Jean Pinsolle, Eug\'enie Terreaux, Christ\`ele Morisseau, Jean-Philippe Ovarlez, Chengfang Ren Out-of-Distribution Radar Detection with Complex VAEs: Theory, Whitening, and ANMF Fusion https://arxiv.org/abs/2601.18677

Olof Hallqvist Elias, Michael Selby, Phillip Stanley-Marbell Distributional Computational Graphs: Error Bounds https://arxiv.org/abs/2601.16250

Behzad Aalipur, Yichen Qin Perfect Clustering for Sparse Directed Stochastic Block Models https://arxiv.org/abs/2601.16427

Fabian Bleile, Sarah Lumpp, Mathias Drton Efficient Learning of Stationary Diffusions with Stein-type Discrepancies https://arxiv.org/abs/2601.16597

Eichi Uehara Robust X-Learner: Breaking the Curse of Imbalance and Heavy Tails via Robust Cross-Imputation https://arxiv.org/abs/2601.15360

Jason Bohne, Ieva Petrulionyte, Michael Arbel, Julien Mairal, Pawe{\l} Polak Non-Stationary Functional Bilevel Optimization https://arxiv.org/abs/2601.15363

Saptarshi Roy, Alessandro Rinaldo, Purnamrita Sarkar Low-Dimensional Adaptation of Rectified Flow: A New Perspective through the Lens of Diffusion and Stochastic Localization https://arxiv.org/abs/2601.15500

Jingfu Peng, Yuhong Yang On damage of interpolation to adversarial robustness in regression https://arxiv.org/abs/2601.16070

Zhengchi Ma, Anru R. Zhang Synthetic Augmentation in Imbalanced Learning: When It Helps, When It Hurts, and How Much to Add https://arxiv.org/abs/2601.16120

Yiyao Yang Beyond Predictive Uncertainty: Reliable Representation Learning with Structural Constraints https://arxiv.org/abs/2601.16174

Peter Potaptchik, Adhi Saravanan, Abbas Mammadov, Alvaro Prat, Michael S. Albergo, Yee Whye Teh Meta Flow Maps enable scalable reward alignment https://arxiv.org/abs/2601.14430

Zhengang Zhong, Yury Korolev, Matthew Thorpe Large Data Limits of Laplace Learning for Gaussian Measure Data in Infinite Dimensions https://arxiv.org/abs/2601.14515

Ziwen Wang, Siqi Li, Marcus Eng Hock Ong, Nan Liu Communication-Efficient Federated Risk Difference Estimation for Time-to-Event Clinical Outcomes https://arxiv.org/abs/2601.14609

Jinyang Liao, Ziyang Lyu Semi-Supervised Mixture Models under the Concept of Missing at Radom with Margin Confidence and Aranda Ordaz Function https://arxiv.org/abs/2601.14631

Michelle Ching, Ioana Popescu, Nico Smith, Tianyi Ma, William G. Underwood, Richard J. Samworth Efficient and Minimax-optimal In-context Nonparametric Regression with Transformers https://arxiv.org/abs/2601.15014

Kexin Wang, Salil Bhate, Jo\~ao M. Pereira, Joe Kileel, Matylda Figlerowicz, Anna Seigal Multi-context principal component analysis https://arxiv.org/abs/2601.15239

Felix Schur, Niklas Pfister, Peng Ding, Sach Mukherjee, Jonas Peters Many Experiments, Few Repetitions, Unpaired Data, and Sparse Effects: Is Causal Inference Possible? https://arxiv.org/abs/2601.15254

Kai Ming Ting, Ye Zhu, Hang Zhang, Tianrun Liang Mass Distribution versus Density Distribution in the Context of Clustering https://arxiv.org/abs/2601.10759

Minseo Kang, Seunghwan Park, Dongha Kim Memorize Early, Then Query: Inlier-Memorization-Guided Active Outlier Detection https://arxiv.org/abs/2601.10993

Fenglin Zhang, Jie Wang Contextual Distributionally Robust Optimization with Causal and Continuous Structure: An Interpretable and Tractable Approach https://arxiv.org/abs/2601.11016

Hangjin Jiang, Yuzhou Li, Zhaoxing Gao Split-and-Conquer: Distributed Factor Modeling for High-Dimensional Matrix-Variate Time Series https://arxiv.org/abs/2601.11091

Nawaf Bou-Rabee, Siddharth Mitra, Andre Wibisono Tail-Sensitive KL and R\'enyi Convergence of Unadjusted Hamiltonian Monte Carlo via One-Shot Couplings https://arxiv.org/abs/2601.09019

Nick Polson, Vadim Sokolov Horseshoe Mixtures-of-Experts (HS-MoE) https://arxiv.org/abs/2601.09043

Hao Qiu (UNIMI), Mengxiao Zhang (CRIStAL), Juliette Achddou (CRIStAL) Decentralized Online Convex Optimization with Unknown Feedback Delays https://arxiv.org/abs/2601.07901

Roy Shivam Ram Shreshtth, Arnab Hazra, Gourab Mukherjee A Statistical Assessment of Amortized Inference Under Signal-to-Noise Variation and Distribution Shift https://arxiv.org/abs/2601.07944

Xinping Yi, Gaojie Jin, Xiaowei Huang, Shi Jin Towards A Unified PAC-Bayesian Framework for Norm-based Generalization Bounds https://arxiv.org/abs/2601.08100

Pei Heng, Yi Sun, Jianhua Guo Structural Dimension Reduction in Bayesian Networks https://arxiv.org/abs/2601.08236

The Tien Mai Robust low-rank estimation with multiple binary responses using pairwise AUC loss https://arxiv.org/abs/2601.08618

Arturo P\'erez-Peralta, Sandra Ben\'itez-Pe\~na, Rosa E. Lillo On the use of graph models to achieve individual and group fairness https://arxiv.org/abs/2601.08784

Rohan Vitthal Thorat, Rajdip Nayek Machine learning assisted state prediction of misspecified linear dynamical system via modal reduction https://arxiv.org/abs/2601.05297

Qiao Liu, Wing Hung Wong A Bayesian Generative Modeling Approach for Arbitrary Conditional Inference https://arxiv.org/abs/2601.05355

Getachew K. Befekadu A brief note on learning problem with global perspectives https://arxiv.org/abs/2601.05441

Yigitcan Comlek, R. Murali Krishnan, Sandipp Krishnan Ravi, Amin Moghaddas, Rafael Giorjao, Michael Eff, Anirban Samaddar, Nesar S. Ramachandra, Sandeep Madireddy, Liping Wang Multi-task Modeling for Engineering Applications with Sparse Data https://arxiv.org/abs/2601.05910

Sunia Tanweer, Firas A. Khasawneh Detecting Stochasticity in Discrete Signals via Nonparametric Excursion Theorem https://arxiv.org/abs/2601.06009

Johanna Tengler, Christoph Brune, Jos\'e A. Iglesias Manifold limit for the training of shallow graph convolutional neural networks https://arxiv.org/abs/2601.06025

Jungi Lee, Jungkwon Kim, Chi Zhang, Sangmin Kim, Kwangsun Yoo, Seok-Joo Byun Mitigating Long-Tailed Anomaly Score Distributions with Importance-Weighted Loss https://arxiv.org/abs/2601.02440

Naixin Guo, Rui Luo, Zhixin Zhou Fast Conformal Prediction using Conditional Interquantile Intervals https://arxiv.org/abs/2601.02769

Juli\'an Tachella, Mike Davies Self-Supervised Learning from Noisy and Incomplete Data https://arxiv.org/abs/2601.03244

Zeyu Bian, Max Biggs, Ruijiang Gao, Zhengling Qi Beyond Demand Estimation: Consumer Surplus Evaluation via Cumulative Propensity Weights https://arxiv.org/abs/2601.01029

Ernest Fokou\'e Fibonacci-Driven Recursive Ensembles: Algorithms, Convergence, and Learning Dynamics https://arxiv.org/abs/2601.01055

Xuan Son Nguyen, Shuo Yang, Aymeric Histace Neural Networks on Symmetric Spaces of Noncompact Type https://arxiv.org/abs/2601.01097

Johan Hallberg Szabadv\'ary Conformal Blindness: A Note on $A$-Cryptic change-points https://arxiv.org/abs/2601.01147

Kalyaan Rao Evidence Slopes and Effective Dimension in Singular Linear Models https://arxiv.org/abs/2601.01238