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

Target-Aware Generative Augmentations for Single-Shot Adaptation ICML 2023
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift NIPS 2023
Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift NIPS 2023
(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy NIPS 2023
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? NIPS 2023
Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability ICML 2023
Beware of Model Collapse! Fast and Stable Test-time Adaptation for Robust Question Answering EMNLP 2023
On the Powerfulness of Textual Outlier Exposure for Visual OoD Detection NIPS 2023
Conservative Offline Policy Adaptation in Multi-Agent Games NIPS 2023
Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting ICML 2023
Adversarial Learning for Feature Shift Detection and Correction NIPS 2023
Test-Time Style Shifting: Handling Arbitrary Styles in Domain Generalization ICML 2023
On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets NIPS 2023
Benchmarking Distribution Shift in Tabular Data with TableShift NIPS 2023
LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning NIPS 2023
In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation ICML 2023
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts ICML 2023
Generalizing Importance Weighting to A Universal Solver for Distribution Shift Problems NIPS 2023
Uncovering Adversarial Risks of Test-Time Adaptation ICML 2023
Estimating Semantic Similarity between In-Domain and Out-of-Domain Samples ACL 2023
Diagnosis, Feedback, Adaptation: A Human-in-the-Loop Framework for Test-Time Policy Adaptation ICML 2023
Reliable learning in challenging environments NIPS 2023
Learning useful representations for shifting tasks and distributions ICML 2023
Auditing Fairness by Betting NIPS 2023
Personalized Semantics Excitation for Federated Image Classification ICCV 2023