A Direct Approach to Robust Deep Learning Using Adversarial Networks

23 May 2019

Papers citing "A Direct Approach to Robust Deep Learning Using Adversarial Networks"

7 / 7 papers shown

Title
DTA: Distribution Transform-based Attack for Query-Limited Scenario Renyang Liu Wei Zhou Xin Jin Song Gao Yuanyu Wang Ruxin Wang 18 0 0 12 Dec 2023
Better Diffusion Models Further Improve Adversarial Training Zekai Wang Tianyu Pang Chao Du Min-Bin Lin Weiwei Liu Shuicheng Yan DiffM 24 208 0 09 Feb 2023
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Saeed Mian Navid Kardan M. Shah AAML 26 235 0 01 Aug 2021
A Robust Adversarial Network-Based End-to-End Communications System With Strong Generalization Ability Against Adversarial Attacks Yudi Dong Huaxia Wang Yu-dong Yao AAML GAN 16 5 0 03 Mar 2021
Increasing-Margin Adversarial (IMA) Training to Improve Adversarial Robustness of Neural Networks Linhai Ma Liang Liang AAML 23 18 0 19 May 2020
Data-Free Network Quantization With Adversarial Knowledge Distillation Yoojin Choi Jihwan P. Choi Mostafa El-Khamy Jungwon Lee MQ 16 119 0 08 May 2020
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 261 3,109 0 04 Nov 2016