conftrace_

distribution shift

722 papers

Explore in graph

Also known as

DS

Co-occurring keywords

domain adaptation (4595) domain generalization (1522) out-of-distribution detection (617) test-time adaptation (312) out-of-distribution generalization (408) causal inference (1630) representation learning (6206) transfer learning (5449) covariate shift (157) graph neural network (3962)

Papers

GAPX: Generalized Autoregressive Paraphrase-Identification X NIPS 2022
Quality Not Quantity: On the Interaction between Dataset Design and Robustness of CLIP NIPS 2022
Domain Generalization without Excess Empirical Risk NIPS 2022
Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective NIPS 2022
Assessing Combinational Generalization of Language Models in Biased Scenarios AACL 2022
Benchmarking the Covariate Shift Robustness of Open-world Intent Classification Approaches AACL 2022
GalilAI: Out-of-Task Distribution Detection using Causal Active Experimentation for Safe Transfer RL AISTATS 2022
Causally motivated shortcut removal using auxiliary labels AISTATS 2022
Calibrated ensembles can mitigate accuracy tradeoffs under distribution shift UAI 2022
DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation AAAI 2022
Tracking Most Significant Arm Switches in Bandits COLT 2022
Minimax Regret Optimization for Robust Machine Learning under Distribution Shift COLT 2022
Robust and Resource-Efficient Data-Free Knowledge Distillation by Generative Pseudo Replay AAAI 2022
Variance Minimization in the Wasserstein Space for Invariant Causal Prediction AISTATS 2022
MEMO: Test Time Robustness via Adaptation and Augmentation NIPS 2022
Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift NIPS 2022
How to Learn when Data Gradually Reacts to Your Model AISTATS 2022
Fast Distributionally Robust Learning with Variance-Reduced Min-Max Optimization AISTATS 2022
An Information-theoretical Approach to Semi-supervised Learning under Covariate-shift AISTATS 2022
Deepchecks: A Library for Testing and Validating Machine Learning Models and Data JMLR 2022
Toward learning human-aligned cross-domain robust models by countering misaligned features UAI 2022
Underspecification Presents Challenges for Credibility in Modern Machine Learning JMLR 2022
Wide Neural Networks Forget Less Catastrophically ICML 2022
Learning To Generate the Unknowns as a Remedy to the Open-Set Domain Shift WACV 2022
Generalization and Robustness Implications in Object-Centric Learning ICML 2022