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Out-of-Distribution Detection

161 directly classified papers

Papers per year

Papers

Watermarking for Out-of-distribution Detection NIPS 2022
RankFeat: Rank-1 Feature Removal for Out-of-distribution Detection NIPS 2022
Agreement-on-the-line: Predicting the Performance of Neural Networks under Distribution Shift NIPS 2022
Boosting Out-of-distribution Detection with Typical Features NIPS 2022
Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs NIPS 2022
OpenAUC: Towards AUC-Oriented Open-Set Recognition NIPS 2022
Provably Adversarially Robust Detection of Out-of-Distribution Data (Almost) for Free NIPS 2022
GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs NIPS 2022
Out-of-Distribution Detection via Conditional Kernel Independence Model NIPS 2022
Is Out-of-Distribution Detection Learnable? NIPS 2022
Amodal Segmentation Through Out-of-Task and Out-of-Distribution Generalization With a Bayesian Model CVPR 2022
PixMix: Dreamlike Pictures Comprehensively Improve Safety Measures CVPR 2022
ViM: Out-of-Distribution With Virtual-Logit Matching CVPR 2022
Class-Aware Contrastive Semi-Supervised Learning CVPR 2022
Evaluating the Practical Utility of Confidence-score based Techniques for Unsupervised Open-world Classification ACL 2022
UniNL: Aligning Representation Learning with Scoring Function for OOD Detection via Unified Neighborhood Learning EMNLP 2022
OpenOOD: Benchmarking Generalized Out-of-Distribution Detection NIPS 2022
Enhancing Out-of-Distribution Detection in Natural Language Understanding via Implicit Layer Ensemble EMNLP 2022
Disentangling Confidence Score Distribution for Out-of-Domain Intent Detection with Energy-Based Learning EMNLP 2022
LUNA: Localizing Unfamiliarity Near Acquaintance for Open-Set Long-Tailed Recognition AAAI 2022
iDECODe: In-Distribution Equivariance for Conformal Out-of-Distribution Detection AAAI 2022
Provable Guarantees for Understanding Out-of-Distribution Detection AAAI 2022
Out of Distribution Data Detection Using Dropout Bayesian Neural Networks AAAI 2022
Exploiting Mixed Unlabeled Data for Detecting Samples of Seen and Unseen Out-of-Distribution Classes AAAI 2022
Topological Uncertainty: Monitoring Trained Neural Networks through Persistence of Activation Graphs IJCAI 2021