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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus · 2013
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Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy · 2014
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A method for stochastic optimization
D Kingma and J Ba Adam · 2015
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Identity mappings in deep residual networks
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Synthesizing robust adversarial examples
Anish Athalye and Ilya Sutskever · 2017
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Towards evaluating the robustness of neural networks
Nicholas Carlini and David Wagner · 2017
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Formal guarantees on the robustness of a classifier against adversarial manipulation
Matthias Hein and Maksym Andriushchenko · 2017
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Conditional variance penalties and domain shift robustness
Christina Heinze-Deml and Nicolai Meinshausen · 2017
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Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2017
Cited alongside, same era.
Practical black-box attacks against machine learning
Nicolas Papernot, Patrick McDaniel, Ian Goodfellow, Somesh Jha, Z Berkay Celik, and Ananthram Swami · 2017
Cited alongside, same era.
On the Robustness of the CVPR 2018 White-Box Adversarial Example Defenses
Anish Athalye and Nicholas Carlini · 2018
Cited alongside, same era.
Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples
Anish Athalye, Nicholas Carlini, and David A. Wagner · 2018
Cited alongside, same era.
Thermometer encoding: One hot way to resist adversarial examples
Jacob Buckman, Aurko Roy, Colin Raffel, and Ian Goodfellow · 2018
Cited alongside, same era.
Technical report on the cleverhans v2.1.0 adversarial examples library
Nicolas Papernot, Fartash Faghri, Nicholas Carlini, Ian Goodfellow, Reuben Feinman, Alexey Kurakin, Cihang Xie, Yash Sharma, Tom Brown, Aurko Roy, Alexander Matyasko, Vahid Behzadan, Karen Hambardzumyan, Zhishuai Zhang, Yi-Lin Juang, Zhi Li, Ryan Sheatsley, Abhibhav Garg, Jonathan Uesato, Willi Gierke, Yinpeng Dong, David Berthelot, Paul Hendricks, Jonas Rauber, and Rujun Long · 2018
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Certified defenses against adversarial examples
Aditi Raghunathan, Jacob Steinhardt, and Percy Liang · 2018
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Adversarial risk and the dangers of evaluating against weak attacks
Jonathan Uesato, Brendan O’Donoghue, Aaron van den Oord, and Pushmeet Kohli · 2018
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Provable defenses against adversarial examples via the convex outer adversarial polytope
Eric Wong and Zico Kolter · 2018
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Provable robustness of relu networks via maximization of linear regions
Francesco Croce, Maksym Andriushchenko, and Matthias Hein · 2018
Cited alongside, same era.
Evaluating and understanding the robustness of adversarial logit pairing
Logan Engstrom, Andrew Ilyas, and Anish Athalye · 2018
Cited alongside, same era.
Harini Kannan, Alexey Kurakin, and Ian Goodfellow · 2018
Cited alongside, same era.
Eric Wong, Frank Schmidt, Jan Hendrik Metzen, and J Zico Kolter · 2018
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Training for faster adversarial robustness verification via inducing relu stability
Kai Y Xiao, Vincent Tjeng, Nur Muhammad Shafiullah, and Aleksander Madry · 2018
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Hessian-based analysis of large batch training and robustness to adversaries
Zhewei Yao, Amir Gholami, Qi Lei, Kurt Keutzer, and Michael W Mahoney · 2018
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Efficient neural network robustness certification with general activation functions
Huan Zhang, Tsui-Wei Weng, Pin-Yu Chen, Cho-Jui Hsieh, and Luca Daniel · 2018
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