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out-of-distribution detection

617 papers

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Also known as

OODD OOD DETECTION

Co-occurring keywords

uncertainty quantification (1393) distribution shift (722) uncertainty estimation (648) anomaly detection (747) neural network (6616) ood detection (45) generative model (2892) representation learning (6206) domain generalization (1522) contrastive learning (4032)

Papers

Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications NIPS 2021
Locally Most Powerful Bayesian Test for Out-of-Distribution Detection using Deep Generative Models NIPS 2021
POODLE: Improving Few-shot Learning via Penalizing Out-of-Distribution Samples NIPS 2021
Improving Compositionality of Neural Networks by Decoding Representations to Inputs NIPS 2021
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable? ICML 2021
On complementing end-to-end human behavior predictors with planning RSS 2021
Improving Robustness and Uncertainty Modelling in Neural Ordinary Differential Equations WACV 2021
Sketching curvature for efficient out-of-distribution detection for deep neural networks UAI 2021
Know your limits: Uncertainty estimation with ReLU classifiers fails at reliable OOD detection UAI 2021
Identifying untrustworthy predictions in neural networks by geometric gradient analysis UAI 2021
Unsupervised anomaly detection with adversarial mirrored autoencoders UAI 2021
Detecting Anomalous Event Sequences with Temporal Point Processes NIPS 2021
Out-of-Distribution Intent Detection with Self-Supervision and Discriminative Training ACL 2021
Open-set Label Noise Can Improve Robustness Against Inherent Label Noise NIPS 2021
LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes NIPS 2021
Triggering Failures: Out-of-Distribution Detection by Learning From Local Adversarial Attacks in Semantic Segmentation ICCV 2021
Semantically Coherent Out-of-Distribution Detection ICCV 2021
Weakly-supervised Temporal Action Localization by Uncertainty Modeling AAAI 2021
Towards a Unifying Framework for Formal Theories of Novelty AAAI 2021
On the Out-of-distribution Generalization of Probabilistic Image Modelling NIPS 2021
NGC: A Unified Framework for Learning With Open-World Noisy Data ICCV 2021
Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection NIPS 2021
On the Importance of Gradients for Detecting Distributional Shifts in the Wild NIPS 2021
ODIST: Open World Classification via Distributionally Shifted Instances EMNLP 2021
MOOD: Multi-Level Out-of-Distribution Detection CVPR 2021