Towards Understanding Adversarial Examples Systematically: Exploring Data Size, Task and Model Factors
Authors: Ke Sun, Zhanxing Zhu, Zhouchen Lin | Published: 2019-02-28
ロバスト性評価
Function Space Particle Optimization for Bayesian Neural Networks
Authors: Ziyu Wang, Tongzheng Ren, Jun Zhu, Bo Zhang | Published: 2019-02-26 | Updated: 2019-05-08
Adversarial attacks hidden in plain sight
Authors: Jan Philip Göpfert, André Artelt, Heiko Wersing, Barbara Hammer | Published: 2019-02-25 | Updated: 2020-04-26
A Convex Relaxation Barrier to Tight Robustness Verification of Neural Networks
Authors: Hadi Salman, Greg Yang, Huan Zhang, Cho-Jui Hsieh, Pengchuan Zhang | Published: 2019-02-23 | Updated: 2020-01-10
The Limitations of Model Uncertainty in Adversarial Settings
Authors: Kathrin Grosse, David Pfaff, Michael Thomas Smith, Michael Backes | Published: 2018-12-06 | Updated: 2019-11-17
Prior Networks for Detection of Adversarial Attacks
Authors: Andrey Malinin, Mark Gales | Published: 2018-12-06
Are Generative Classifiers More Robust to Adversarial Attacks?
Authors: Yingzhen Li, John Bradshaw, Yash Sharma | Published: 2018-02-19 | Updated: 2019-05-27
Certified Robustness to Adversarial Examples with Differential Privacy
Authors: Mathias Lecuyer, Vaggelis Atlidakis, Roxana Geambasu, Daniel Hsu, Suman Jana | Published: 2018-02-09 | Updated: 2019-05-29
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach
Authors: Tsui-Wei Weng, Huan Zhang, Pin-Yu Chen, Jinfeng Yi, Dong Su, Yupeng Gao, Cho-Jui Hsieh, Luca Daniel | Published: 2018-01-31