conftrace_

distribution shift

722 papers

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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

Finetune Like You Pretrain: Improved Finetuning of Zero-Shot Vision Models CVPR 2023
Balanced Product of Calibrated Experts for Long-Tailed Recognition CVPR 2023
DetAIL: A Tool to Automatically Detect and Analyze Drift in Language AAAI 2023
Learning To Retain While Acquiring: Combating Distribution-Shift in Adversarial Data-Free Knowledge Distillation CVPR 2023
Seasoning Model Soups for Robustness to Adversarial and Natural Distribution Shifts CVPR 2023
Probing Out-of-Distribution Robustness of Language Models with Parameter-Efficient Transfer Learning ACL 2023
Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capability ICML 2023
Auditing Fairness by Betting NIPS 2023
A Closer Look at the Robustness of Contrastive Language-Image Pre-Training (CLIP) NIPS 2023
SoTTA: Robust Test-Time Adaptation on Noisy Data Streams NIPS 2023
Beyond Invariance: Test-Time Label-Shift Adaptation for Addressing "Spurious" Correlations NIPS 2023
Generalizing Importance Weighting to A Universal Solver for Distribution Shift Problems NIPS 2023
Reliable learning in challenging environments NIPS 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
Adversarial Learning for Feature Shift Detection and Correction NIPS 2023
LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning NIPS 2023
Instance-Dependent Generalization Bounds via Optimal Transport JMLR 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
Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift NIPS 2023
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? NIPS 2023
On the Powerfulness of Textual Outlier Exposure for Visual OoD Detection NIPS 2023
FedFed: Feature Distillation against Data Heterogeneity in Federated Learning NIPS 2023
Mutual Information Regularized Offline Reinforcement Learning NIPS 2023