Characterizing out-of-distribution generalization of neural networks: application to the disordered Su–Schrieffer–Heeger model by Kacper Cybiński, Marcin Płodzień, Michał Tomza, Maciej Lewenstein, Alexandre Dauphin, Anna Dawid

Subjects: “…out-of-distribution generalization…”
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First, Do No Harm: Addressing AI's Challenges With Out‐of‐Distribution Data in Medicine by Chu Weng, Wesley Lin, Sherry Dong, Qi Liu, Hanrui Zhang

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Machine and deep learning performance in out-of-distribution regressions by Assaf Shmuel, Oren Glickman, Teddy Lazebnik

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Unsupervised Anomaly Detection With Variational Autoencoders Applied to Full‐Disk Solar Images by Marius Giger, André Csillaghy

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