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Distribution Shift

190 directly classified papers

Papers per year

Papers

Certifying Some Distributional Fairness with Subpopulation Decomposition NIPS 2022
Anticipating Performativity by Predicting from Predictions NIPS 2022
ORIENT: Submodular Mutual Information Measures for Data Subset Selection under Distribution Shift NIPS 2022
Transferring Fairness under Distribution Shifts via Fair Consistency Regularization NIPS 2022
JAWS: Auditing Predictive Uncertainty Under Covariate Shift NIPS 2022
MEMO: Test Time Robustness via Adaptation and Augmentation NIPS 2022
DASCO: Dual-Generator Adversarial Support Constrained Offline Reinforcement Learning NIPS 2022
Distribution Alignment: A Unified Framework for Long-Tail Visual Recognition CVPR 2021
DAT: Training Deep Networks Robust To Label-Noise by Matching the Feature Distributions CVPR 2021
Don’t Discard All the Biased Instances: Investigating a Core Assumption in Dataset Bias Mitigation Techniques EMNLP 2021
Towards a Theoretical Framework of Out-of-Distribution Generalization NIPS 2021
Integrated Latent Heterogeneity and Invariance Learning in Kernel Space NIPS 2021
IRM—when it works and when it doesn't: A test case of natural language inference NIPS 2021
An Information-theoretic Approach to Distribution Shifts NIPS 2021
Evaluating model performance under worst-case subpopulations NIPS 2021
Recovering Latent Causal Factor for Generalization to Distributional Shifts NIPS 2021
A nonparametric method for gradual change problems with statistical guarantees NIPS 2021
Overparameterization Improves Robustness to Covariate Shift in High Dimensions NIPS 2021
ODIST: Open World Classification via Distributionally Shifted Instances EMNLP 2021
AutoDO: Robust AutoAugment for Biased Data With Label Noise via Scalable Probabilistic Implicit Differentiation CVPR 2021
MOS: Towards Scaling Out-of-Distribution Detection for Large Semantic Space CVPR 2021
Does enforcing fairness mitigate biases caused by subpopulation shift? NIPS 2021
Deep Stable Learning for Out-of-Distribution Generalization CVPR 2021
Stable Adversarial Learning under Distributional Shifts AAAI 2021
Accurate and Robust Feature Importance Estimation under Distribution Shifts AAAI 2021