conftrace_

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

Why Normalizing Flows Fail to Detect Out-of-Distribution Data NIPS 2020
Debugging Tests for Model Explanations NIPS 2020
Detecting Out-of-Distribution Examples with Gram Matrices ICML 2020
Defending Against Model Stealing Attacks With Adaptive Misinformation CVPR 2020
Uncertainty Estimation Using a Single Deep Deterministic Neural Network ICML 2020
Detecting Semantic Anomalies AAAI 2020
Selective Question Answering under Domain Shift ACL 2020
Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder NIPS 2020
Uncertainty-Aware Deep Classifiers Using Generative Models AAAI 2020
Convolutional Neural Networks with Compression Complexity Pooling for Out-of-Distribution Image Detection IJCAI 2020
REST: Performance Improvement of a Black Box Model via RL-Based Spatial Transformation AAAI 2020
Certifiably Adversarially Robust Detection of Out-of-Distribution Data NIPS 2020
Self-Supervised Learning for Generalizable Out-of-Distribution Detection AAAI 2020
Semi-Supervised Learning under Class Distribution Mismatch AAAI 2020
Towards Maximizing the Representation Gap between In-Domain & Out-of-Distribution Examples NIPS 2020
Uncertainty Aware Semi-Supervised Learning on Graph Data NIPS 2020
Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles AAAI 2020
OOD-MAML: Meta-Learning for Few-Shot Out-of-Distribution Detection and Classification NIPS 2020
Unsupervised Out-of-Distribution Detection by Maximum Classifier Discrepancy ICCV 2019
Likelihood Ratios for Out-of-Distribution Detection NIPS 2019
Modeling Uncertainty by Learning a Hierarchy of Deep Neural Connections NIPS 2019
Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty NIPS 2019
Accurate Layerwise Interpretable Competence Estimation NIPS 2019
Learning and the Unknown: Surveying Steps toward Open World Recognition AAAI 2019
Building Trust in Deep Learning System towards Automated Disease Detection AAAI 2019