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Out of distribution (OOD) detection is a crucial part of making machine learning systems robust.
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Natural adversarial examples
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J. Ren, P. J. Liu, E. Fertig, J. Snoek, R. Poplin, M. A. DePristo, J. V. Dillon, and B. Lakshminarayanan · 2019
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Generalized odin: Detecting out-of-distribution image without learning from out-of-distribution data, 2020
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Enhancing the reliability of out-of-distribution image detection in neural networks, 2020
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Pretrained models https://github.com/cadene/pretrained-models.pytorch
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Tiny image net https://image-net.org/download.php
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No true state-of-the-art? ood detection methods are inconsistent across datasets, 2021
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L. H. Zhang, M. Goldstein, and R. Ranganath · 2021
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