distribution shift

Effective Robustness against Natural Distribution Shifts for Models with Different Training Data NeurIPS 2023 Empowering Graph Representation Learning with Test-Time Graph Transformation ICLR 2023 Enhancing Multiple Reliability Measures via Nuisance-Extended Information Bottleneck CVPR 2023 Ensemble-based Deep Reinforcement Learning for Vehicle Routing Problems under Distribution Shift NeurIPS 2023 Estimating Semantic Similarity between In-Domain and Out-of-Domain Samples ACL 2023 Evading DeepFake Detectors via Adversarial Statistical Consistency CVPR 2023 Evolving Standardization for Continual Domain Generalization over Temporal Drift NeurIPS 2023 Fair Densities via Boosting the Sufficient Statistics of Exponential Families ICML 2023 FedFed: Feature Distillation against Data Heterogeneity in Federated Learning NeurIPS 2023 Finetune Like You Pretrain: Improved Finetuning of Zero-Shot Vision Models CVPR 2023 Freeze then Train: Towards Provable Representation Learning under Spurious Correlations and Feature Noise AISTATS 2023 Generalizing Importance Weighting to A Universal Solver for Distribution Shift Problems NeurIPS 2023 Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting ICML 2023 GeoNet: Benchmarking Unsupervised Adaptation Across Geographies CVPR 2023 GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-Distribution Generalization Perspective ACL 2023 Graph-Structured Gaussian Processes for Transferable Graph Learning NeurIPS 2023 Hedging against Complexity: Distributionally Robust Optimization with Parametric Approximation AISTATS 2023 How hard are computer vision datasets? Calibrating dataset difficulty to viewing time NeurIPS 2023 How robust is unsupervised representation learning to distribution shift? ICLR 2023 HybridAugment++: Unified Frequency Spectra Perturbations for Model Robustness ICCV 2023 HYDRA: Hybrid Robot Actions for Imitation Learning CoRL 2023 ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets NeurIPS 2023 Identifying Selection Bias from Observational Data AAAI 2023 Imitation Learning from Imperfection: Theoretical Justifications and Algorithms NeurIPS 2023 Improved Online Conformal Prediction via Strongly Adaptive Online Learning ICML 2023