Robust width: A lightweight and certifiable adversarial defense
J Peck, B Goossens - arXiv preprint arXiv:2405.15971, 2024 - arxiv.org
Deep neural networks are vulnerable to so-called adversarial examples: inputs which are
intentionally constructed to cause the model to make incorrect predictions or classifications …
intentionally constructed to cause the model to make incorrect predictions or classifications …