134 citations · 153 across the 3 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2019★ 19 cited
Is AmI (Attacks Meet Interpretability) Robust to Adversarial Examples?
Nicholas Carlini
No.
cs.LG2019★ 134 cited
Adversarial Examples Are a Natural Consequence of Test Error in Noise
Nic Ford, Justin Gilmer, Nicolas Carlini +1
Over the last few years, the phenomenon of adversarial examples --- maliciously constructed inputs that fool trained machine learning models --- has captured the attention of the r…