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Generalisation in humans and deep neural networks

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Towards the first adversarially robust neural network model on MNIST., , , and . ICLR (Poster), OpenReview.net, (2019)Scaling up the Randomized Gradient-Free Adversarial Attack Reveals Overestimation of Robustness Using Established Attacks., , and . Int. J. Comput. Vis., 128 (4): 1028-1046 (2020)EagerPy: Writing Code That Works Natively with PyTorch, TensorFlow, JAX, and NumPy, , and . (2020)cite arxiv:2008.04175.Advances in Reliably Evaluating and Improving Adversarial Robustness.. University of Tübingen, Germany, (2021)Foolbox v0.8.0: A Python toolbox to benchmark the robustness of machine learning models., , and . CoRR, (2017)Robust Perception through Analysis by Synthesis., , , and . CoRR, (2018)Generalisation in humans and deep neural networks, , , , , and . Advances in Neural Information Processing Systems, page 7549--7561. (2018)Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models., , and . ICLR (Poster), OpenReview.net, (2018)Accurate, reliable and fast robustness evaluation., , , , and . NeurIPS, page 12841-12851. (2019)Generalisation in humans and deep neural networks., , , , , and . NeurIPS, page 7549-7561. (2018)