Strength in Numbers: Trading-off Robustness and Computation via Adversarially-Trained Ensembles

22 November 2018

Papers citing "Strength in Numbers: Trading-off Robustness and Computation via Adversarially-Trained Ensembles"

8 / 8 papers shown

Title
Data Augmentation Can Improve Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 31 270 0 09 Nov 2021
How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review Florian Tambon Gabriel Laberge Le An Amin Nikanjam Paulina Stevia Nouwou Mindom Y. Pequignot Foutse Khomh G. Antoniol E. Merlo François Laviolette 37 66 0 26 Jul 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 32 65 0 09 Apr 2021
Fixing Data Augmentation to Improve Adversarial Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 36 270 0 02 Mar 2021
Adversarial Training with Stochastic Weight Average Joong-won Hwang Youngwan Lee Sungchan Oh Yuseok Bae OOD AAML 29 11 0 21 Sep 2020
Beat the AI: Investigating Adversarial Human Annotation for Reading Comprehension Max Bartolo A. Roberts Johannes Welbl Sebastian Riedel Pontus Stenetorp AAML 28 167 0 02 Feb 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,675 0 05 Dec 2016
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 296 3,112 0 04 Nov 2016