Towards Interpretable Deep Neural Networks by Leveraging Adversarial Examples

18 August 2017

Yinpeng Dong

Hang Su

Jun Zhu

Fan Bao

AAML

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Papers citing "Towards Interpretable Deep Neural Networks by Leveraging Adversarial Examples"

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Title
Robust Explainable Recommendation Sairamvinay Vijayaraghavan Prasant Mohapatra AAML 23 0 0 03 May 2024
Black-Box Access is Insufficient for Rigorous AI Audits Stephen Casper Carson Ezell Charlotte Siegmann Noam Kolt Taylor Lynn Curtis ... Michael Gerovitch David Bau Max Tegmark David M. Krueger Dylan Hadfield-Menell AAML 20 76 0 25 Jan 2024
Rethinking Model Ensemble in Transfer-based Adversarial Attacks Huanran Chen Yichi Zhang Yinpeng Dong Xiao Yang Hang Su Junyi Zhu AAML 26 55 0 16 Mar 2023
Multi-concept adversarial attacks Vibha Belavadi Yan Zhou Murat Kantarcioglu B. Thuraisingham AAML 28 0 0 19 Oct 2021
Robust Feature-Level Adversaries are Interpretability Tools Stephen Casper Max Nadeau Dylan Hadfield-Menell Gabriel Kreiman AAML 40 27 0 07 Oct 2021
EX-RAY: Distinguishing Injected Backdoor from Natural Features in Neural Networks by Examining Differential Feature Symmetry Yingqi Liu Guangyu Shen Guanhong Tao Zhenting Wang Shiqing Ma X. Zhang AAML 22 8 0 16 Mar 2021
A Unified Game-Theoretic Interpretation of Adversarial Robustness Jie Ren Die Zhang Yisen Wang Lu Chen Zhanpeng Zhou ... Xu Cheng Xin Eric Wang Meng Zhou Jie Shi Quanshi Zhang AAML 64 22 0 12 Mar 2021
Theory-guided hard constraint projection (HCP): a knowledge-based data-driven scientific machine learning method Yuntian Chen Dou Huang Dongxiao Zhang Junsheng Zeng Nanzhe Wang Haoran Zhang Jinyue Yan PINN 34 106 0 11 Dec 2020
Learning Black-Box Attackers with Transferable Priors and Query Feedback Jiancheng Yang Yangzhou Jiang Xiaoyang Huang Bingbing Ni Chenglong Zhao AAML 12 81 0 21 Oct 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 27 62 0 11 Sep 2020
Adversarial Attacks and Defenses: An Interpretation Perspective Ninghao Liu Mengnan Du Ruocheng Guo Huan Liu Xia Hu AAML 24 8 0 23 Apr 2020
Adversarial Ranking Attack and Defense Mo Zhou Zhenxing Niu Le Wang Qilin Zhang G. Hua 28 38 0 26 Feb 2020
A Framework for Explainable Text Classification in Legal Document Review Christian J. Mahoney Jianping Zhang Nathaniel Huber-Fliflet Peter Gronvall Haozhen Zhao AILaw 14 32 0 19 Dec 2019
Interpretable Few-Shot Learning via Linear Distillation Arip Asadulaev Igor Kuznetsov Andrey Filchenkov FedML FAtt 11 1 0 13 Jun 2019
Interpreting Adversarially Trained Convolutional Neural Networks Tianyuan Zhang Zhanxing Zhu AAML GAN FAtt 19 157 0 23 May 2019
Testing DNN Image Classifiers for Confusion & Bias Errors Yuchi Tian Ziyuan Zhong Vicente Ordonez Gail E. Kaiser Baishakhi Ray 16 52 0 20 May 2019
Interpreting Adversarial Examples by Activation Promotion and Suppression Kaidi Xu Sijia Liu Gaoyuan Zhang Mengshu Sun Pu Zhao Quanfu Fan Chuang Gan X. Lin AAML FAtt 10 43 0 03 Apr 2019
Explanation Methods in Deep Learning: Users, Values, Concerns and Challenges Gabrielle Ras Marcel van Gerven W. Haselager XAI 17 217 0 20 Mar 2018
Bioinformatics and Medicine in the Era of Deep Learning D. Bacciu P. Lisboa José D. Martín R. Stoean A. Vellido AI4CE BDL 33 17 0 27 Feb 2018
Understanding and Enhancing the Transferability of Adversarial Examples Lei Wu Zhanxing Zhu Cheng Tai E. Weinan AAML SILM 22 96 0 27 Feb 2018
Intriguing Properties of Randomly Weighted Networks: Generalizing While Learning Next to Nothing Amir Rosenfeld John K. Tsotsos MLT 24 51 0 02 Feb 2018
Interpretation of Neural Networks is Fragile Amirata Ghorbani Abubakar Abid James Y. Zou FAtt AAML 22 856 0 29 Oct 2017
Boosting Adversarial Attacks with Momentum Yinpeng Dong Fangzhou Liao Tianyu Pang Hang Su Jun Zhu Xiaolin Hu Jianguo Li AAML 24 83 0 17 Oct 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 261 3,109 0 04 Nov 2016
Do semantic parts emerge in Convolutional Neural Networks? Abel Gonzalez-Garcia Davide Modolo V. Ferrari 150 113 0 13 Jul 2016