A Research Agenda: Dynamic Models to Defend Against Correlated Attacks

14 March 2019

Papers citing "A Research Agenda: Dynamic Models to Defend Against Correlated Attacks"

9 / 9 papers shown

Title
AI Control: Improving Safety Despite Intentional Subversion Ryan Greenblatt Buck Shlegeris Kshitij Sachan Fabien Roger 31 40 0 12 Dec 2023
PubDef: Defending Against Transfer Attacks From Public Models Chawin Sitawarin Jaewon Chang David Huang Wesson Altoyan David Wagner AAML 39 6 0 26 Oct 2023
Towards Out-of-Distribution Adversarial Robustness Adam Ibrahim Charles Guille-Escuret Ioannis Mitliagkas Irina Rish David M. Krueger P. Bashivan OOD 31 6 0 06 Oct 2022
Towards Evaluating the Robustness of Neural Networks Learned by Transduction Jiefeng Chen Xi Wu Yang Guo Yingyu Liang S. Jha ELM AAML 20 15 0 27 Oct 2021
Morphence: Moving Target Defense Against Adversarial Examples Abderrahmen Amich Birhanu Eshete AAML 27 24 0 31 Aug 2021
Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks Dequan Wang An Ju Evan Shelhamer David Wagner Trevor Darrell AAML 26 27 0 18 May 2021
Anomalous Example Detection in Deep Learning: A Survey Saikiran Bulusu B. Kailkhura Bo-wen Li P. Varshney D. Song AAML 28 47 0 16 Mar 2020
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Zhehuai Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 718 6,750 0 26 Sep 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 317 5,847 0 08 Jul 2016