Adversarial Attacks on Variational Autoencoders

12 Jun 2018George Gondim-RibeiroPedro TabacofEduardo Valle

Adversarial attacks are malicious inputs that derail machine-learning models. We propose a scheme to attack autoencoders, as well as a quantitative evaluation framework that correlates well with the qualitative assessment of the attacks... (read more)

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