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Provably Adversarially Robust Detection of Out-of-Distribution Data (Almost) for Free.

, , и . NeurIPS, (2022)

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Matthias Hein

Matthias Hein

Matthias Hein

Matthias Hein

Matthias Hein

 

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Error Estimates for Spectral Convergence of the Graph Laplacian on Random Geometric Graphs Toward the Laplace-Beltrami Operator., , , и . Found. Comput. Math., 20 (4): 827-887 (2020)Adversarial Robustness on In- and Out-Distribution Improves Explainability., , и . ECCV (26), том 12371 из Lecture Notes in Computer Science, стр. 228-245. Springer, (2020)The loss surface and expressivity of deep convolutional neural networks., и . ICLR (Workshop), OpenReview.net, (2018)Towards neural networks that provably know when they don't know., и . CoRR, (2019)On Mitigating Random and Adversarial Bit Errors., , , и . CoRR, (2020)A Unifying Perron-Frobenius Theorem for Nonnegative Tensors via Multihomogeneous Maps., , и . SIAM J. Matrix Anal. Appl., 40 (3): 1206-1231 (2019)Disentangling Adversarial Robustness and Generalization., , и . CoRR, (2018)Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure DNN Accelerators., , , и . CoRR, (2021)Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks., , и . ICML, том 119 из Proceedings of Machine Learning Research, стр. 9155-9166. PMLR, (2020)Provably Adversarially Robust Detection of Out-of-Distribution Data (Almost) for Free., , и . NeurIPS, (2022)