Revisiting Classifier Two-Sample Tests

20 October 2016

Maxime Oquab

Papers citing "Revisiting Classifier Two-Sample Tests"

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Title
Boosting Statistic Learning with Synthetic Data from Pretrained Large Models Jialong Jiang Wenkang Hu Jian Huang Yuling Jiao Xu Liu DiffM 45 0 0 08 May 2025
What's Wrong with Your Synthetic Tabular Data? Using Explainable AI to Evaluate Generative Models Jan Kapar Niklas Koenen Martin Jullum 64 0 0 29 Apr 2025
Revisiting Data Auditing in Large Vision-Language Models Hongyu Zhu Sichu Liang W. Wang Boheng Li Tongxin Yuan Fangqi Li Shilin Wang Zhuosheng Zhang VLM 152 0 0 25 Apr 2025
H2ST: Hierarchical Two-Sample Tests for Continual Out-of-Distribution Detection Yuhang Liu Wenjie Zhao Yunhui Guo OODD 58 0 0 19 Mar 2025
Robust Simulation-Based Inference under Missing Data via Neural Processes Yogesh Verma Ayush Bharti Vikas K. Garg 63 0 0 03 Mar 2025
Multifidelity Simulation-based Inference for Computationally Expensive Simulators Anastasia N. Krouglova Hayden R. Johnson Basile Confavreux Michael Deistler P. J. Gonçalves 73 1 0 17 Feb 2025
An efficient likelihood-free Bayesian inference method based on sequential neural posterior estimation Yifei Xiong Xiliang Yang Sanguo Zhang Zhijian He 108 2 0 17 Jan 2025
A Unified Data Representation Learning for Non-parametric Two-sample Testing Xunye Tian Liuhua Peng Zhijian Zhou M. Gong Feng Liu Feng Liu 82 0 0 30 Nov 2024
Compositional simulation-based inference for time series Manuel Gloeckler S. Toyota Kenji Fukumizu Jakob H Macke 37 1 0 05 Nov 2024
Learning Deep Kernels for Non-Parametric Independence Testing Nathaniel Xu Feng Liu Danica J. Sutherland BDL 29 0 0 10 Sep 2024
Convolutional L2LFlows: Generating Accurate Showers in Highly Granular Calorimeters Using Convolutional Normalizing Flows Thorsten Buss F. Gaede Gregor Kasieczka Claudius Krause David Shih AI4CE 28 6 0 30 May 2024
Collaborative non-parametric two-sample testing Alejandro de la Concha Nicolas Vayatis Argyris Kalogeratos 21 0 0 08 Feb 2024
Leveraging Nested MLMC for Sequential Neural Posterior Estimation with Intractable Likelihoods Xiliang Yang Yifei Xiong Zhijian He 21 0 0 30 Jan 2024
Unified framework for diffusion generative models in SO(3): applications in computer vision and astrophysics Yesukhei Jagvaral F. Lanusse Rachel Mandelbaum DiffM 28 5 0 18 Dec 2023
Deep anytime-valid hypothesis testing T. Pandeva Patrick Forré Aaditya Ramdas S. Shekhar 22 3 0 30 Oct 2023
Kernel-Based Testing for Single-Cell Differential Analysis Anthony Ozier-Lafontaine Camille Fourneaux G. Durif Polina Arsenteva C. Vallot O. Gandrillon Sandrine Giraud Bertrand Michel Franck Picard 13 5 0 17 Jul 2023
The Representation Jensen-Shannon Divergence J. Hoyos-Osorio Santiago Posso-Murillo L. S. Giraldo 37 6 0 25 May 2023
Membership Inference Attacks against Synthetic Data through Overfitting Detection B. V. Breugel Hao Sun Zhaozhi Qian M. Schaar 19 45 0 24 Feb 2023
Boosting the Power of Kernel Two-Sample Tests Anirban Chatterjee B. Bhattacharya 32 3 0 21 Feb 2023
Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference Ryan P. Kelly David J. Nott David T. Frazier D. Warne Christopher C. Drovandi 20 10 0 31 Jan 2023
Active Sequential Two-Sample Testing Weizhi Li Prad Kadambi Pouria Saidi K. Ramamurthy Gautam Dasarathy Visar Berisha VLM 26 1 0 30 Jan 2023
MAUVE Scores for Generative Models: Theory and Practice Krishna Pillutla Lang Liu John Thickstun Sean Welleck Swabha Swayamdipta Rowan Zellers Sewoong Oh Yejin Choi Zaïd Harchaoui EGVM 23 21 0 30 Dec 2022
Measuring the Measuring Tools: An Automatic Evaluation of Semantic Metrics for Text Corpora George Kour Samuel Ackerman Orna Raz E. Farchi Boaz Carmeli Ateret Anaby-Tavor 34 10 0 29 Nov 2022
MMD-B-Fair: Learning Fair Representations with Statistical Testing Namrata Deka Danica J. Sutherland 11 6 0 15 Nov 2022
DC-Check: A Data-Centric AI checklist to guide the development of reliable machine learning systems Nabeel Seedat F. Imrie M. Schaar 27 12 0 09 Nov 2022
Autoregressive 3D Shape Generation via Canonical Mapping A. Cheng Xueting Li Sifei Liu Min Sun Ming Yang 3DPC 37 39 0 05 Apr 2022
Variational methods for simulation-based inference Manuel Glöckler Michael Deistler Jakob H. Macke 25 46 0 08 Mar 2022
SPAGHETTI: Editing Implicit Shapes Through Part Aware Generation Amir Hertz Or Perel Raja Giryes O. Sorkine-Hornung Daniel Cohen-Or 33 26 0 31 Jan 2022
Group equivariant neural posterior estimation Maximilian Dax Stephen R. Green J. Gair Michael Deistler Bernhard Schölkopf Jakob H. Macke BDL 31 31 0 25 Nov 2021
Test for non-negligible adverse shifts Vathy M. Kamulete 13 3 0 07 Jul 2021
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals Lang Liu Krishna Pillutla Sean Welleck Sewoong Oh Yejin Choi Zaïd Harchaoui MQ 22 14 0 15 Jun 2021
Meta Two-Sample Testing: Learning Kernels for Testing with Limited Data Feng Liu Wenkai Xu Jie Lu Danica J. Sutherland 8 19 0 14 Jun 2021
CaloFlow: Fast and Accurate Generation of Calorimeter Showers with Normalizing Flows Claudius Krause David Shih AI4CE 13 81 0 09 Jun 2021
Fair Representations by Compression Xavier Gitiaux Huzefa Rangwala FaML 17 14 0 28 May 2021
Large Scale Image Completion via Co-Modulated Generative Adversarial Networks Shengyu Zhao Jianwei Cui Yilun Sheng Yue Dong Xiao Liang E. Chang Yan Xu 34 290 0 18 Mar 2021
Learning to Generate 3D Shapes with Generative Cellular Automata Dongsu Zhang Changwoon Choi Jeonghwan Kim Y. Kim 23 24 0 06 Mar 2021
Two-sample Test with Kernel Projected Wasserstein Distance Jie Wang Rui Gao Yao Xie 14 19 0 12 Feb 2021
MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers Krishna Pillutla Swabha Swayamdipta Rowan Zellers John Thickstun Sean Welleck Yejin Choi Zaïd Harchaoui 26 341 0 02 Feb 2021
GUIGAN: Learning to Generate GUI Designs Using Generative Adversarial Networks Tianming Zhao Chunyang Chen Yuanning Liu Xiaodong Zhu Jilin University 27 56 0 25 Jan 2021
Benchmarking Simulation-Based Inference Jan-Matthis Lueckmann Jan Boelts David S. Greenberg P. J. Gonçalves Jakob H. Macke 96 184 0 12 Jan 2021
On the Evaluation of Generative Adversarial Networks By Discriminative Models A. Torfi Mohammadreza Beyki Edward A. Fox EGVM 11 7 0 07 Oct 2020
Parallelizing MCMC Sampling via Space Partitioning V. Hafych P. Eller O. Schulz Allen Caldwel 24 4 0 07 Aug 2020
Progressive Point Cloud Deconvolution Generation Network Le Hui Rui Xu Jin Xie J. Qian Jian Yang 3DPC 11 72 0 10 Jul 2020
Learning Deep Kernels for Non-Parametric Two-Sample Tests Feng Liu Wenkai Xu Jie Lu Guangquan Zhang A. Gretton Danica J. Sutherland 11 176 0 21 Feb 2020
Towards GAN Benchmarks Which Require Generalization Ishaan Gulrajani Colin Raffel Luke Metz 11 57 0 10 Jan 2020
A discriminative approach for finding and characterizing positivity violations using decision trees Ehud Karavani Peter Bak Y. Shimoni 22 3 0 18 Jul 2019
PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows Guandao Yang Xun Huang Zekun Hao Ming-Yu Liu Serge J. Belongie Bharath Hariharan 3DPC 11 654 0 28 Jun 2019
Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting Aditya Grover Jiaming Song Alekh Agarwal Kenneth Tran Ashish Kapoor Eric Horvitz Stefano Ermon 24 123 0 23 Jun 2019
Balanced off-policy evaluation in general action spaces A. Sondhi David Arbour Drew Dimmery OffRL 13 17 0 09 Jun 2019
Fair Division Without Disparate Impact A. Peysakhovich Christian Kroer 14 10 0 06 Jun 2019