401 citations · 1.6k across the 64 of their papers we have counts for
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Learning Transferable Adversarial Examples via Ghost Networks
Yingwei Li, Song Bai, Yuyin Zhou +3
Recent development of adversarial attacks has proven that ensemble-based methods outperform traditional, non-ensemble ones in black-box attack. However, as it is computationally pr…
Feature Denoising for Improving Adversarial Robustness
Cihang Xie, Yuxin Wu, Laurens van der Maaten +2
Adversarial attacks to image classification systems present challenges to convolutional networks and opportunities for understanding them. This study suggests that adversarial pert…
Adversarial Attacks and Defences Competition
Alexey Kurakin, Ian Goodfellow, Samy Bengio +20
To accelerate research on adversarial examples and robustness of machine learning classifiers, Google Brain organized a NIPS 2017 competition that encouraged researchers to develop…
Improving Transferability of Adversarial Examples with Input Diversity
Cihang Xie, Zhishuai Zhang, Yuyin Zhou +4
Though CNNs have achieved the state-of-the-art performance on various vision tasks, they are vulnerable to adversarial examples --- crafted by adding human-imperceptible perturbati…