Metrics and methods for robustness evaluation of neural networks with generative models

4 Mar 2020Igor BuzhinskyArseny NerinovskyStavros Tripakis

Recent studies have shown that modern deep neural network classifiers are easy to fool, assuming that an adversary is able to slightly modify their inputs. Many papers have proposed adversarial attacks, defenses and methods to measure robustness to such adversarial perturbations... (read more)

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