Agreement-on-the-Line: Predicting the Performance of Neural Networks
under Distribution Shift

Agreement-on-the-Line: Predicting the Performance of Neural Networks under Distribution Shift

27 June 2022

Aditi Raghunathan

Papers citing "Agreement-on-the-Line: Predicting the Performance of Neural Networks under Distribution Shift"

18 / 18 papers shown

Title
Performance Estimation in Binary Classification Using Calibrated Confidence Juhani Kivimäki Jakub Białek W. Kuberski J. Nurminen 50 0 0 08 May 2025
Always Tell Me The Odds: Fine-grained Conditional Probability Estimation Liaoyaqi Wang Zhengping Jiang Anqi Liu Benjamin Van Durme 61 0 0 02 May 2025
UNEM: UNrolled Generalized EM for Transductive Few-Shot Learning Long Zhou Fereshteh Shakeri Aymen Sadraoui Mounir Kaaniche J. Pesquet Ismail Ben Ayed VLM 86 0 0 21 Dec 2024
What Does Softmax Probability Tell Us about Classifiers Ranking Across Diverse Test Conditions? Weijie Tu Weijian Deng Liang Zheng Tom Gedeon 40 0 0 14 Jun 2024
Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization Mahyar Fazlyab Taha Entesari Aniket Roy Ramalingam Chellappa AAML 16 11 0 29 Sep 2023
Anchor Points: Benchmarking Models with Much Fewer Examples Rajan Vivek Kawin Ethayarajh Diyi Yang Douwe Kiela ALM 29 22 0 14 Sep 2023
Learning Diverse Features in Vision Transformers for Improved Generalization A. Nicolicioiu Andrei Liviu Nicolicioiu B. Alexe Damien Teney 33 3 0 30 Aug 2023
Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources Feiyang Kang H. Just Anit Kumar Sahu R. Jia 59 10 0 05 Jul 2023
Confidence-Based Model Selection: When to Take Shortcuts for Subpopulation Shifts Annie S. Chen Yoonho Lee Amrith Rajagopal Setlur Sergey Levine Chelsea Finn OOD 16 5 0 19 Jun 2023
DC4L: Distribution Shift Recovery via Data-Driven Control for Deep Learning Models Vivian Lin Kuk Jin Jang Souradeep Dutta Michele Caprio O. Sokolsky Insup Lee OOD 31 6 0 20 Feb 2023
Demystifying Disagreement-on-the-Line in High Dimensions Dong-Hwan Lee Behrad Moniri Xinmeng Huang Yan Sun Hamed Hassani 21 8 0 31 Jan 2023
Assaying Out-Of-Distribution Generalization in Transfer Learning F. Wenzel Andrea Dittadi Peter V. Gehler Carl-Johann Simon-Gabriel Max Horn ... Chris Russell Thomas Brox Bernt Schiele Bernhard Schölkopf Francesco Locatello OOD OODD AAML 60 71 0 19 Jul 2022
On the Strong Correlation Between Model Invariance and Generalization Weijian Deng Stephen Gould Liang Zheng OOD 32 16 0 14 Jul 2022
A Note on "Assessing Generalization of SGD via Disagreement" Andreas Kirsch Y. Gal FedML UQCV 23 15 0 03 Feb 2022
High-Performance Large-Scale Image Recognition Without Normalization Andrew Brock Soham De Samuel L. Smith Karen Simonyan VLM 223 512 0 11 Feb 2021
Bottleneck Transformers for Visual Recognition A. Srinivas Nayeon Lee Niki Parmar Jonathon Shlens Pieter Abbeel Ashish Vaswani SLR 290 979 0 27 Jan 2021
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 297 10,220 0 16 Nov 2016
Domain Adaptation: Learning Bounds and Algorithms Yishay Mansour M. Mohri Afshin Rostamizadeh 179 789 0 19 Feb 2009