out-of-distribution detection

Detecting Semantic Anomalies AAAI 2020 Domain Adaptive Image-to-Image Translation CVPR 2020 Efficient Out-of-Distribution Detection in Digital Pathology Using Multi-Head Convolutional Neural Networks MIDL 2020 Energy-based Out-of-distribution Detection NeurIPS 2020 Ensemble Distribution Distillation ICLR 2020 Flows for simultaneous manifold learning and density estimation NeurIPS 2020 Generalized ODIN: Detecting Out-of-Distribution Image Without Learning From Out-of-Distribution Data CVPR 2020 Improving Confidence Estimates for Unfamiliar Examples CVPR 2020 Input Complexity and Out-of-distribution Detection with Likelihood-based Generative Models ICLR 2020 Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder NeurIPS 2020 Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles AAAI 2020 NADS: Neural Architecture Distribution Search for Uncertainty Awareness ICML 2020 Novelty Detection Via Blurring ICLR 2020 OOD-MAML: Meta-Learning for Few-Shot Out-of-Distribution Detection and Classification NeurIPS 2020 Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts NeurIPS 2020 REST: Performance Improvement of a Black Box Model via RL-Based Spatial Transformation AAAI 2020 Robust Learning Through Cross-Task Consistency CVPR 2020 Selective Question Answering under Domain Shift ACL 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 NeurIPS 2020 Towards neural networks that provably know when they don't know ICLR 2020 Training Normalizing Flows with the Information Bottleneck for Competitive Generative Classification NeurIPS 2020 Uncertainty-Aware Deep Classifiers Using Generative Models AAAI 2020 Uncertainty Aware Semi-Supervised Learning on Graph Data NeurIPS 2020