"covariate shift" Papers
25 papers found
Conference
$\Delta \mathrm{Energy}$: Optimizing Energy Change During Vision-Language Alignment Improves both OOD Detection and OOD Generalization
Lin Zhu, Yifeng Yang, Xinbing Wang et al.
Are Sparse Autoencoders Useful? A Case Study in Sparse Probing
Subhash Kantamneni, Josh Engels, Senthooran Rajamanoharan et al.
Benign Overfitting in Out-of-Distribution Generalization of Linear Models
Shange Tang, Jiayun Wu, Jianqing Fan et al.
BirdSet: A Large-Scale Dataset for Audio Classification in Avian Bioacoustics
Lukas Rauch, Raphael Schwinger, Moritz Wirth et al.
DisCoPatch: Taming Adversarially-driven Batch Statistics for Improved Out-of-Distribution Detection
Francisco Caetano, Christiaan Viviers, Luis Zavala-Mondragón et al.
Estimating Model Performance Under Covariate Shift Without Labels
Jakub Białek, Juhani Kivimäki, Wojciech Kuberski et al.
ETA: Energy-based Test-time Adaptation for Depth Completion
Younjoon Chung, Hyoungseob Park, Patrick Rim et al.
Extending Foundational Monocular Depth Estimators to Fisheye Cameras with Calibration Tokens
Suchisrit Gangopadhyay, Jung Hee Kim, Xien Chen et al.
Graph Data Selection for Domain Adaptation: A Model-Free Approach
Ting-Wei Li, Ruizhong Qiu, Hanghang Tong
Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift
Zhen Zhang, Xin Liu, Shaoli Wang et al.
Pseudo-Labeling for Kernel Ridge Regression under Covariate Shift
Kaizheng Wang
Quantifying Uncertainty in the Presence of Distribution Shifts
Yuli Slavutsky, David Blei
Regressing the Relative Future: Efficient Policy Optimization for Multi-turn RLHF
Zhaolin Gao, Wenhao Zhan, Jonathan Chang et al.
Transfer Learning for Benign Overfitting in High-Dimensional Linear Regression
Yeichan Kim, Ilmun Kim, Seyoung Park
Wasserstein-Regularized Conformal Prediction under General Distribution Shift
Rui Xu, Chao Chen, Yue Sun et al.
Conformal Validity Guarantees Exist for Any Data Distribution (and How to Find Them)
Drew Prinster, Samuel Stanton, Anqi Liu et al.
CRoFT: Robust Fine-Tuning with Concurrent Optimization for OOD Generalization and Open-Set OOD Detection
Lin Zhu, Yifeng Yang, Qinying Gu et al.
Fairness under Covariate Shift: Improving Fairness-Accuracy Tradeoff with Few Unlabeled Test Samples
Shreyas Havaldar, Jatin Chauhan, Karthikeyan Shanmugam et al.
High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization
Yihang Chen, Fanghui Liu, Taiji Suzuki et al.
Minimum-Norm Interpolation Under Covariate Shift
Neil Mallinar, Austin Zane, Spencer Frei et al.
Not all distributional shifts are equal: Fine-grained robust conformal inference
Jiahao Ai, Zhimei Ren
Optimal Ridge Regularization for Out-of-Distribution Prediction
Pratik Patil, Jin-Hong Du, Ryan Tibshirani
Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift
Benjamin Eyre, Elliot Creager, David Madras et al.
TEA: Test-time Energy Adaptation
Yige Yuan, Bingbing Xu, Liang Hou et al.
Test-Time Adaptation for Depth Completion
Hyoungseob Park, Anjali W Gupta, Alex Wong