And/or trade-off in artificial neurons: impact on adversarial robustness

15 February 2021

Papers citing "And/or trade-off in artificial neurons: impact on adversarial robustness"

10 / 10 papers shown

Title
Adversarial Examples Are Not Bugs, They Are Features Andrew Ilyas Shibani Santurkar Dimitris Tsipras Logan Engstrom Brandon Tran Aleksander Madry SILM 89 1,837 0 06 May 2019
Adversarial Training for Free! Ali Shafahi Mahyar Najibi Amin Ghiasi Zheng Xu John P. Dickerson Christoph Studer L. Davis Gavin Taylor Tom Goldstein AAML 125 1,245 0 29 Apr 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 130 2,036 0 08 Feb 2019
Certified Adversarial Robustness with Additive Noise Bai Li Changyou Chen Wenlin Wang Lawrence Carin AAML 91 346 0 10 Sep 2018
Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models Wojciech Samek Thomas Wiegand K. Müller XAI VLM 68 1,189 0 28 Aug 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 283 12,060 0 19 Jun 2017
Comment on "Biologically inspired protection of deep networks from adversarial attacks" Wieland Brendel Matthias Bethge AAML 80 34 0 05 Apr 2017
On Detecting Adversarial Perturbations J. H. Metzen Tim Genewein Volker Fischer Bastian Bischoff AAML 61 950 0 14 Feb 2017
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 517 5,893 0 08 Jul 2016
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 253 14,912 1 21 Dec 2013