A Learning Based Hypothesis Test for Harmful Covariate Shift

6 December 2022

Papers citing "A Learning Based Hypothesis Test for Harmful Covariate Shift"

28 / 28 papers shown

Title
Predicting Out-of-Distribution Error with the Projection Norm Yaodong Yu Zitong Yang Alexander Wei Yi-An Ma Jacob Steinhardt OODD 45 44 0 11 Feb 2022
Leveraging Unlabeled Data to Predict Out-of-Distribution Performance Saurabh Garg Sivaraman Balakrishnan Zachary Chase Lipton Behnam Neyshabur Hanie Sedghi OODD OOD 62 130 0 11 Jan 2022
Deep Neural Networks and Tabular Data: A Survey V. Borisov Tobias Leemann Kathrin Seßler Johannes Haug Martin Pawelczyk Gjergji Kasneci LMTD 112 687 0 05 Oct 2021
Mind the Performance Gap: Examining Dataset Shift During Prospective Validation Erkin Ötleş Jeeheh Oh Benjamin Li Michelle Bochinski Hyeon Joo ... E. Shenoy L. Washer V. Young Krishna Rao Jenna Wiens OOD 38 15 0 23 Jul 2021
Understanding Failures in Out-of-Distribution Detection with Deep Generative Models Lily H. Zhang Mark Goldstein Rajesh Ranganath OODD 167 105 0 14 Jul 2021
A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection Jie Jessie Ren Stanislav Fort J. Liu Abhijit Guha Roy Shreyas Padhy Balaji Lakshminarayanan UQCV 170 225 0 16 Jun 2021
Efficient Learning with Arbitrary Covariate Shift Adam Kalai Varun Kanade 43 8 0 15 Feb 2021
WILDS: A Benchmark of in-the-Wild Distribution Shifts Pang Wei Koh Shiori Sagawa Henrik Marklund Sang Michael Xie Marvin Zhang ... A. Kundaje Emma Pierson Sergey Levine Chelsea Finn Percy Liang OOD 177 1,433 0 14 Dec 2020
Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples S. Goldwasser Adam Tauman Kalai Y. Kalai Omar Montasser AAML 45 40 0 10 Jul 2020
Density of States Estimation for Out-of-Distribution Detection Warren Morningstar Cusuh Ham Andrew Gallagher Balaji Lakshminarayanan Alexander A. Alemi Joshua V. Dillon OODD 76 84 0 16 Jun 2020
Learning Deep Kernels for Non-Parametric Two-Sample Tests Feng Liu Wenkai Xu Jie Lu Guangquan Zhang Arthur Gretton Danica J. Sutherland 43 186 0 21 Feb 2020
Likelihood Ratios for Out-of-Distribution Detection Jie Jessie Ren Peter J. Liu Emily Fertig Jasper Snoek Ryan Poplin M. DePristo Joshua V. Dillon Balaji Lakshminarayanan OODD 186 722 0 07 Jun 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 167 1,695 0 06 Jun 2019
Do ImageNet Classifiers Generalize to ImageNet? Benjamin Recht Rebecca Roelofs Ludwig Schmidt Vaishaal Shankar OOD SSeg VLM 113 1,715 0 13 Feb 2019
SelectiveNet: A Deep Neural Network with an Integrated Reject Option Yonatan Geifman Ran El-Yaniv CVBM OOD 123 311 0 26 Jan 2019
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift Stephan Rabanser Stephan Günnemann Zachary Chase Lipton 59 368 0 29 Oct 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks Kimin Lee Kibok Lee Honglak Lee Jinwoo Shin OODD 185 2,051 0 10 Jul 2018
Rotation Equivariant CNNs for Digital Pathology Bastiaan S. Veeling J. Linmans Jim Winkens Taco S. Cohen Max Welling 109 582 0 08 Jun 2018
Do CIFAR-10 Classifiers Generalize to CIFAR-10? Benjamin Recht Rebecca Roelofs Ludwig Schmidt Vaishaal Shankar OOD FedML ELM 166 412 0 01 Jun 2018
Detecting and Correcting for Label Shift with Black Box Predictors Zachary Chase Lipton Yu Wang Alex Smola OOD 63 554 0 12 Feb 2018
Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks Shiyu Liang Yixuan Li R. Srikant UQCV OODD 168 2,069 0 08 Jun 2017
Deep Sets Manzil Zaheer Satwik Kottur Siamak Ravanbakhsh Barnabás Póczós Ruslan Salakhutdinov Alex Smola 405 2,464 0 10 Mar 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 831 5,821 0 05 Dec 2016
Revisiting Classifier Two-Sample Tests David Lopez-Paz Maxime Oquab 155 402 0 20 Oct 2016
XGBoost: A Scalable Tree Boosting System Tianqi Chen Carlos Guestrin 802 38,961 0 09 Mar 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.8K 150,115 0 22 Dec 2014
Deep Learning Face Attributes in the Wild Ziwei Liu Ping Luo Xiaogang Wang Xiaoou Tang CVBM 244 8,408 0 28 Nov 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 452 16,933 0 20 Dec 2013