Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural
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Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network

1 October 2018

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Papers citing "Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network"

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Title
ML-LOO: Detecting Adversarial Examples with Feature Attribution Puyudi Yang Jianbo Chen Cho-Jui Hsieh Jane-ling Wang Michael I. Jordan AAML 98 101 0 08 Jun 2019
Adversarially Robust Generalization Just Requires More Unlabeled Data Runtian Zhai Tianle Cai Di He Chen Dan Kun He John E. Hopcroft Liwei Wang 98 158 0 03 Jun 2019
NATTACK: Learning the Distributions of Adversarial Examples for an Improved Black-Box Attack on Deep Neural Networks Yandong Li Lijun Li Liqiang Wang Tong Zhang Boqing Gong AAML 101 245 0 01 May 2019
Adversarial Robustness vs Model Compression, or Both? Shaokai Ye Kaidi Xu Sijia Liu Jan-Henrik Lambrechts Huan Zhang Aojun Zhou Kaisheng Ma Yanzhi Wang Xue Lin AAML 114 165 0 29 Mar 2019
Robust Decision Trees Against Adversarial Examples Hongge Chen Huan Zhang Duane S. Boning Cho-Jui Hsieh AAML 142 117 0 27 Feb 2019
The Limitations of Model Uncertainty in Adversarial Settings Kathrin Grosse David Pfaff M. Smith Michael Backes AAML 63 34 0 06 Dec 2018
Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness against Adversarial Attack Adnan Siraj Rakin Zhezhi He Deliang Fan AAML 69 292 0 22 Nov 2018