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Deep learning models are known to be vulnerable to adversarial attacks. Adversarial learning is therefore becoming a crucial task. We propose a new vision on neural network robustness using Riemannian geometry and foliat...
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Robustness of deep neural networks is a critical issue in practical applications. In the case of deep dense neural networks, under random noise attacks, we propose to study the probability that the output of the network ...