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

Estimating Generalization under Distribution Shifts via Domain-Invariant Representations ICML 2020
Label-Noise Robust Domain Adaptation ICML 2020
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts ICML 2020
The MAGICAL Benchmark for Robust Imitation NIPS 2020
The Effect of Natural Distribution Shift on Question Answering Models ICML 2020
A Unified View of Label Shift Estimation NIPS 2020
Hidden Risks of Machine Learning Applied to Healthcare: Unintended Feedback Loops Between Models and Future Data Causing Model Degradation MLHC 2020
Pretrained Transformers Improve Out-of-Distribution Robustness ACL 2020
On the Value of Out-of-Distribution Testing: An Example of Goodhart's Law NIPS 2020
Stochastic Optimization for Performative Prediction NIPS 2020
Posterior Re-calibration for Imbalanced Datasets NIPS 2020
On the Trade-off between Adversarial and Backdoor Robustness NIPS 2020
Measuring Robustness to Natural Distribution Shifts in Image Classification NIPS 2020
Rethinking Importance Weighting for Deep Learning under Distribution Shift NIPS 2020
Generalized ODIN: Detecting Out-of-Distribution Image Without Learning From Out-of-Distribution Data CVPR 2020
Learning with Feature and Distribution Evolvable Streams ICML 2020
Towards Accurate and Robust Domain Adaptation under Noisy Environments IJCAI 2020
Bridging Causality and Learning: How Do They Benefit from Each Other? IJCAI 2020
On Numerosity of Deep Neural Networks NIPS 2020
Stable Prediction with Model Misspecification and Agnostic Distribution Shift AAAI 2020
Deep Active Learning for Biased Datasets via Fisher Kernel Self-Supervision CVPR 2020
Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution Tests NIPS 2020
LTF: A Label Transformation Framework for Correcting Label Shift ICML 2020
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts? ICML 2020
CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances NIPS 2020