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In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation., , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 2471-2506. PMLR, (2023)Provably Adversarially Robust Detection of Out-of-Distribution Data (Almost) for Free., , and . NeurIPS, (2022)Neural Network Heuristic Functions: Taking Confidence into Account., , , , and . SOCS, page 223-228. AAAI Press, (2022)Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD Training Data Estimate a Combination of the Same Core Quantities., , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 2041-2074. PMLR, (2022)Provably Robust Detection of Out-of-distribution Data (almost) for free., , and . CoRR, (2021)Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem., , and . CVPR Workshops, page 58-74. Computer Vision Foundation / IEEE, (2019)Certifiably Adversarially Robust Detection of Out-of-Distribution Data., , and . NeurIPS, (2020)A Simple Way to Make Neural Networks Robust Against Diverse Image Corruptions., , , , , , and . ECCV (3), volume 12348 of Lecture Notes in Computer Science, page 53-69. Springer, (2020)