Exploring Architectural Ingredients of Adversarially Robust Deep Neural
Networks

Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks

7 October 2021

Quanquan Gu

Papers citing "Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks"

19 / 69 papers shown

Title
Towards Alternative Techniques for Improving Adversarial Robustness: Analysis of Adversarial Training at a Spectrum of Perturbations Kaustubh Sridhar Souradeep Dutta Ramneet Kaur James Weimer O. Sokolsky Insup Lee AAML 16 4 0 13 Jun 2022
FACM: Intermediate Layer Still Retain Effective Features against Adversarial Examples Xiangyuan Yang Jie Lin Hanlin Zhang Xinyu Yang Peng Zhao AAML 26 0 0 02 Jun 2022
Squeeze Training for Adversarial Robustness Qizhang Li Yiwen Guo W. Zuo Hao Chen OOD 26 9 0 23 May 2022
Gradient Concealment: Free Lunch for Defending Adversarial Attacks Sen Pei Jiaxi Sun Xiaopeng Zhang Gaofeng Meng AAML 16 0 0 21 May 2022
Gradient Aligned Attacks via a Few Queries Xiangyuan Yang Jie Lin Hanlin Zhang Xinyu Yang Peng Zhao AAML 17 0 0 19 May 2022
Adversarial Robustness through the Lens of Convolutional Filters Paul Gavrikov J. Keuper 15 15 0 05 Apr 2022
CNN Filter DB: An Empirical Investigation of Trained Convolutional Filters Paul Gavrikov J. Keuper AAML 11 31 0 29 Mar 2022
Self-Ensemble Adversarial Training for Improved Robustness Hongjun Wang Yisen Wang OOD AAML 11 37 0 18 Mar 2022
Enhancing Adversarial Robustness for Deep Metric Learning Mo Zhou Vishal M. Patel AAML 6 18 0 02 Mar 2022
Understanding Adversarial Robustness from Feature Maps of Convolutional Layers Cong Xu Wei Zhang Jun Wang Min Yang AAML 13 2 0 25 Feb 2022
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 181 344 0 15 Dec 2021
RobustART: Benchmarking Robustness on Architecture Design and Training Techniques Shiyu Tang Ruihao Gong Yan Wang Aishan Liu Jiakai Wang ... Xianglong Liu D. Song Alan Yuille Philip H. S. Torr Dacheng Tao VLM AAML 11 105 0 11 Sep 2021
NoiLIn: Improving Adversarial Training and Correcting Stereotype of Noisy Labels Jingfeng Zhang Xilie Xu Bo Han Tongliang Liu Gang Niu Li-zhen Cui Masashi Sugiyama NoLa AAML 10 9 0 31 May 2021
Tiny Adversarial Mulit-Objective Oneshot Neural Architecture Search Guoyang Xie Jinbao Wang Guo-Ding Yu Feng Zheng Yaochu Jin AAML 9 3 0 28 Feb 2021
Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training Lue Tao Lei Feng Jinfeng Yi Sheng-Jun Huang Songcan Chen AAML 13 56 0 09 Feb 2021
With False Friends Like These, Who Can Notice Mistakes? Lue Tao Lei Feng Jinfeng Yi Songcan Chen AAML 11 5 0 29 Dec 2020
Adversarial Momentum-Contrastive Pre-Training Cong Xu Dan Li Min Yang SSL 19 13 0 24 Dec 2020
Imbalanced Gradients: A Subtle Cause of Overestimated Adversarial Robustness Xingjun Ma Linxi Jiang Hanxun Huang Zejia Weng James Bailey Yu-Gang Jiang AAML 12 5 0 24 Jun 2020
Adversarial Camouflage: Hiding Physical-World Attacks with Natural Styles Ranjie Duan Xingjun Ma Yisen Wang James Bailey •. A. K. Qin Yun Yang AAML 142 222 0 08 Mar 2020