mlsanityData to 7 Oct 2026

E-Valuating Classifier Two-Sample Tests

arXiv 2210.13027 ↗First posted 24 Oct 2022stat.ME cs.LG stat.MLcited by 10

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Abstract (arXiv)

We introduce a powerful deep classifier two-sample test for high-dimensional data based on E-values, called E-value Classifier Two-Sample Test (E-C2ST). Our test combines ideas from existing work on split likelihood ratio tests and predictive independence tests. The resulting E-values are suitable for anytime-valid sequential two-sample tests. This feature allows for more effective use of data in constructing test statistics. Through simulations and real data applications, we empirically demonstrate that E-C2ST achieves enhanced statistical power by partitioning datasets into multiple batches beyond the conventional two-split (training and testing) approach of standard classifier two-sample tests. This strategy increases the power of the test while keeping the type I error well below the desired significance level.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 28 of its 61 references that are in the map. First posted on arXiv 24 Oct 2022.

Builds on

28 of 61 references.

References · 28

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2014ImageNet Large Scale Visual Recognition Challengecited by 8,441
  4. 2013Distributed Representations of Words and Phrases and their Compositionalitycited by 3,462
  5. 2015Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networkscited by 2,048
  6. 2018fastMRI: An Open Dataset and Benchmarks for Accelerated MRIcited by 464
  7. 2016Revisiting Classifier Two-Sample Testscited by 258
  8. 2021Benchmarking Simulation-Based Inferencecited by 160
  9. 2022Game-theoretic statistics and safe anytime-valid inferencecited by 145
  10. 2020Learning Deep Kernels for Non-Parametric Two-Sample Testscited by 129
  11. 2019Safe Testingcited by 98
  12. 2016Interpretable Distribution Features with Maximum Testing Powercited by 63
16 more
  1. 2015Fast Two-Sample Testing with Analytic Representations of Probability Measurescited by 53
  2. 2020Active MR k-space Sampling with Reinforcement Learningcited by 45
  3. 2019Universal Inferencecited by 43
  4. 2020Experimental design for MRI by greedy policy searchcited by 40
  5. 2016Classification accuracy as a proxy for two sample testingcited by 39
  6. 2021Nonparametric Two-Sample Testing by Bettingcited by 36
  7. 2019Two-sample Testing Using Deep Learningcited by 26
  8. 2019Classification Logit Two-sample Testing by Neural Networkscited by 25
  9. 2015Sequential Nonparametric Testing with the Law of the Iterated Logarithmcited by 19
  10. 2022On learning adaptive acquisition policies for undersampled multi-coil MRI reconstructioncited by 14
  11. 2022Model-X Sequential Testing for Conditional Independence via Testing by Bettingcited by 14
  12. 2022Anytime Valid Tests of Conditional Independence Under Model-Xcited by 11
  13. 2020Interactive rank testing by bettingcited by 5
  14. 2022Exact Anytime-valid Confidence Intervals for Contingency Tables and Beyondcited by 5
  15. 2017Predictive Independence Testing, Predictive Conditional Independence Testing, and Predictive Graphical Modellingcited by 3
  16. 2020Sharp finite-sample concentration of independent variablescited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 5; 2024: 1; 2025: 2; 2026: 2.

10 papers.

  1. 2023Sequential Predictive Two-Sample and Independence Testingcited by 20
  2. 2023L-C2ST: Local Diagnostics for Posterior Approximations in Simulation-Based Inferencecited by 17
  3. 2024A Practical Guide to Sample-based Statistical Distances for Evaluating Generative Models in Sciencecited by 14
  4. 2025On Continuous Monitoring of Risk Violations under Unknown Shiftcited by 9
  5. 2023Deep anytime-valid hypothesis testingcited by 7
  6. 2025Keeping Medical AI Healthy and Trustworthy: A Review of Detection and Correction Methods for System Degradationcited by 6
  7. 2023Active Sequential Two-Sample Testingcited by 4
  8. 2023Simulation-based Inference with the Generalized Kullback-Leibler Divergencecited by 3
  9. 2026Detecting Performance Degradation under Data Shift in Pathology Vision-Language Modelcited by 1
  10. 2026Sequential Kernel-based Conditional Independence Testing via Adaptive Bettingcited by 0