Two-Sample Testing

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Overview

Two-sample testing asks whether differences between two samples reflect a real change in their underlying distributions or ordinary sampling variation. Common approaches include kernel tests such as maximum mean discrepancy, classifier-based tests, nearest-neighbor and graph statistics, and permutation calibration; newer methods also use learned representations and generative-process dynamics. These tests support applications such as detecting data drift, comparing generative models, and finding changes in images, text, or networks. A central challenge is maintaining reliable false-alarm control while achieving power with high-dimensional, weakly different, or severely imbalanced samples.

Latest papers

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32 papers7 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

  1. Asymmetric Likelihood-Free Hypothesis Testing

    Oct 21, 2026Gunjan Kumar, Yash Pote, Jonathan ScarlettStatistical Hypothesis TestingSample Complexity

    IIT Kanpur · National University of Singapore

  2. From Imbalance to Evidence: Deep Nonparametric Testing for Complex Data under Severe Sample Imbalance

    Oct 9, 2026Guanhao Zhou, Xiufan YuTwo-Sample TestingStatistical Hypothesis Testing

    Department of Applied and Computational Mathematics and Statistics University of Notre Dame

  3. Where Do Two Populations of Persistence Diagrams Differ? Calibrated Local Inference at a Fixed Budget

    Oct 6, 2026Pramita Bagchi, Edward Bae, Atish Mitra +3Two-Sample TestingConfidence Region Estimation

    The George Washington University · Montana Technological University · University of Ljubljana

  4. Two-Sample Testing via Generative Processes

    Oct 6, 2026Eshant English, Kenji Fukumizu, Taiji SuzukiTwo-Sample TestingStatistical Hypothesis Testing

    The University of Tokyo, Tokyo, Japan · Hasso Plattner Institute for Digital Engineering, Germany · Institute of Statistical Mathematics, Japan +1

  5. Beyond Marginal Monitoring: Distributed Joint-Distribution Testing for Data Concept Drift in Large Scale E-Commerce Operations

    Oct 6, 2026Cagdas Pullu, Mahmut Emir Arslan, Bugra Balkac +4Two-Sample TestingConcept Drift

    Data & Analytics, Trendyol Group, Istanbul, 34485, Istanbul, Türkiye. · Department of Data Science and Analytics, Istanbul Technical University, Maslak, Istanbul, 34469, Istanbul, Türkiye.

  6. Two-Sample Testing for Random Graphs without Vertex Correspondence

    Oct 5, 2026Soham DanTwo-Sample TestingStatistical Power Analysis

  7. Two-Sample Testing via Path-based Inference

    Oct 5, 2026Eshant English, Wei-Cheng Lai, Yanfeng Yang +3Two-Sample TestingPermutation Testing

    The University of Tokyo, Tokyo, Japan · Hasso Plattner Institute for Digital Engineering, Germany · Institute of Statistical Mathematics, Japan +3

  8. Two-Sample Testing for Inhomogeneous Random Graphs in Non-Integral LrL_r Norms

    Sep 27, 2026Soham DanTwo-Sample Testing

  9. Localizing Global Discrepancies: Marginal Contributions and Contextual Anomaly Detection

    Aug 28, 2026Tommaso dorigoAnomaly LocalizationAnomaly Detection

    INFN, Sezione di Padova, Padova, Italy · Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, Luleå, Sweden

  10. What FID Hides: Detecting, Ranking, and Diagnosing Deviations in Generative Evaluation

    Aug 25, 2026Hao ChenGenerative AI EvaluationImage Generation Evaluation

    Department of Statistics University of California, Davis

  11. A Shared Encoder Is Not a Shared Task: Conditional Comparison for Deep Expert Pools

    Aug 21, 2026Kentaro OdaTask Transferability EstimationMixture-of-Experts Models

    Center for Management of Information Technologies, Kagoshima University

  12. How fine a change can moments see? A scale law for detecting distribution shift, with a kernel calibration rule

    Aug 2, 2026Adel KalecheTwo-Sample TestingDistribution Shift

    Independent researcher, France

  13. Zero-Flow Two-Sample Tests

    Jul 23, 2026Yakun Wang, Leyang Wang, Song Liu +1Two-Sample TestingStatistical Hypothesis Testing

    University of Bristol · RIKEN AIP · University of Tokyo & RIKEN AIP

  14. Directional Kernel Mean Difference: A Fast Signed Statistic for Univariate Distribution Comparison

    Jul 22, 2026Shijie Zhong, Jiangfeng FuTwo-Sample TestingMaximum Mean Discrepancy

    School of Power and Energy Northwestern Polytechnical University Xi’an, Shanxi 710129

  15. Measuring the Dependency Gap: Diagnosing Inter-Column Fidelity in Tabular Generative Models

    Jul 20, 2026Jie ZhangTwo-Sample TestingSynthetic Tabular Data Generation

    Accenture, Tokyo 107-8672, Japan

  16. ASK-NN: An Asymmetric Nearest-Neighbor Test that detects Distribution Drifts in Natural Language

    Jul 17, 2026Sergey Zakharov, Rodion Oblovatny, Alexey ZaytsevTwo-Sample TestingAI-Generated Text Detection

    Saint-Peterburg university, Saint-Peterburg, Russia · Risk AI Research Lab, Moscow, Russia · Applied AI Institute, Moscow, Russia

  17. USAD: Uncertainty-aware Statistical Adversarial Detection

    Jun 26, 2026Zhijian Zhou, Xunye Tian, Jiacheng Zhang +5Two-Sample TestingAdversarial Example Detection

    The University of Melbourne

  18. A nonparametric two-sample test using a parametric integral probability metric

    Jun 15, 2026Yuha Park, Yongdai KimTwo-Sample TestingStatistical Learning Theory

    Department of Mathematics, University of Hamburg, Hamburg, Germany. · Department of Statistics, Seoul National University, Seoul, Republic of Korea.

  19. From Persistence to Survival: Hypothesis Testing, Effect Sizes and Vectorisation for Topological Features

    Jun 10, 2026Juliette Murris, Bernadette Stolz, Karsten BorgwardtTwo-Sample TestingPersistent Homology

    Department of Machine Learning and Systems Biology, Max Planck Institute of Biochemistry, Martinsried, Germany

  20. LOTTERY: Learning from Reference-Only Samples in Two-Sample Testing under Size Asymmetry

    Jun 7, 2026Xunye Tian, Zhijian Zhou, Liuhua Peng +1Two-Sample TestingPermutation Testing

    University of Melbourne · Maincode

  21. Sharp Low-Degree Thresholds for Planted-vs-Planted Testing

    Jun 3, 2026Anda Skeja, Daniel Gutiérrez Espinoza, Fiona Skerman +1Two-Sample TestingLow-Degree Polynomial Method

    Department of Mathematics, Uppsala University · Department of Mathematics, University of California, Davis

  22. Counterfactual Explanations for Deep Two-Sample Testing

    May 29, 2026Wei-Cheng Lai, Marco Simnacher, Christoph LippertTwo-Sample TestingCounterfactual Explanations

    Digital Health and Machine Learning Hasso-Plattner-Institute, University of Potsdam Potsdam, Germany · Chair of Statistics Humboldt-Universität zu Berlin Berlin, Germany · Hasso Plattner Institute for Digital Health at Mount Sinai Icahn School of Medicine at Mount Sinai New York, United States of America

  23. Detecting Metastable Basins in High Dimensions via Marginal Trajectory Distribution Discrimination

    May 22, 2026Taj Jones-McCormickDynamical SystemsTwo-Sample Testing

  24. Micro-Defects Expose Macro-Fakes: Detecting AI-Generated Images via Local Distributional Shifts

    May 10, 2026Boxuan Zhang, Jianing Zhu, Qifan Wang +2Two-Sample TestingImage Forgery Detection

    Rutgers University · The University of Texas at Austin · Meta AI +1

  25. Accurate and Efficient Statistical Testing for Word Semantic Breadth

    May 8, 2026Yo EharaTwo-Sample TestingPermutation Testing

    Tokyo Gakugei University

  26. Kernel Selection is Model Selection: A Unified Complexity-Penalized Approach for MMD Two-Sample Tests

    May 7, 2026Yijin Ni, Xiaoming HuoModel SelectionTwo-Sample Testing

    H. Milton Stewart School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta, GA 30332, USA

  27. A Semi-Supervised Kernel Two-Sample Test

    May 3, 2026Gyumin Lee, Shubhanshu Shekhar, Ilmun KimTwo-Sample TestingKernel Methods

    Dept. of Statistics Pennsylvania State University · Dept. of EECS University of Michigan · Dept. of Mathematical Sciences KAIST

  28. Phase Transitions as the Breakdown of Statistical Indistinguishability

    Apr 17, 2026Taiyo Narita, Hideyuki MiyaharaTwo-Sample TestingPhase Transitions

    Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Hokkaido 060-0814, Japan

  29. Maximum Mean Discrepancy with Unequal Sample Sizes via Generalized U-Statistics

    Dec 16, 2025Aaron Wei, Milad Jalali, Danica J. SutherlandTwo-Sample TestingMaximum Mean Discrepancy

    University of British Columbia · Independent researcher, Vancouver, Canada · Alberta Machine Intelligence Institute

  30. Classical and quantum kernel fusion for two-sample testing

    Nov 26, 2025Yu Terada, Yugo Ogio, Ken Arai +2Two-Sample TestingMaximum Mean Discrepancy

    Advanced Research Laboratory, Sony Group Corporation, 1-7-1 Konan, Minato-ku, Tokyo 108-0075, Japan · Deloitte Tohmatsu Consulting LLC.