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ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness., , , , , and . ICLR, OpenReview.net, (2019)Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX., , , and . J. Open Source Softw., 5 (53): 2607 (2020)Adversarial Vision Challenge., , , , , , , and . CoRR, (2018)Texture Synthesis Using Shallow Convolutional Networks with Random Filters., , , and . CoRR, (2016)On Adaptive Attacks to Adversarial Example Defenses., , , and . NeurIPS, (2020)Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints., , , and . NeurIPS, page 20052-20062. (2021)Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding., , , , , , and . ICLR, OpenReview.net, (2021)Visual Representation Learning Does Not Generalize Strongly Within the Same Domain., , , , , , , , and . ICLR, OpenReview.net, (2022)What does it take to generate natural textures?, , , and . ICLR (Poster), OpenReview.net, (2017)Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet., and . ICLR (Poster), OpenReview.net, (2019)