364 citations · 942 across the 15 of their papers we have counts for
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cs.CR2017★ 7 cited
How Wrong Am I? - Studying Adversarial Examples and their Impact on Uncertainty in Gaussian Process Machine Learning Models
Kathrin Grosse, David Pfaff, Michael Thomas Smith +1
Machine learning models are vulnerable to Adversarial Examples: minor perturbations to input samples intended to deliberately cause misclassification. Current defenses against adve…
cs.CR2017★ 364 cited
On the (Statistical) Detection of Adversarial Examples
Kathrin Grosse, Praveen Manoharan, Nicolas Papernot +2
Machine Learning (ML) models are applied in a variety of tasks such as network intrusion detection or Malware classification. Yet, these models are vulnerable to a class of malicio…