Towards Robust Deep Neural Networks with BANG

Towards Robust Deep Neural Networks with BANG

1 December 2016

Manuel Günther

Terrance E. Boult

Papers citing "Towards Robust Deep Neural Networks with BANG"

14 / 14 papers shown

Title
Sinkhorn Distributionally Robust Optimization Jie Wang Rui Gao Yao Xie 46 35 0 24 Sep 2021
Simple Post-Training Robustness Using Test Time Augmentations and Random Forest Gilad Cohen Raja Giryes AAML 40 4 0 16 Sep 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Mian Navid Kardan M. Shah AAML 36 236 0 01 Aug 2021
A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined Augmentations Finetuning to Efficiently Improve the Robustness of CNNs Nikhil Kapoor C. Yuan Jonas Löhdefink Roland S. Zimmermann Serin Varghese Fabian Hüger Nico M. Schmidt Peter Schlicht Tim Fingscheidt AAML 27 4 0 02 Dec 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 27 73 0 07 Aug 2020
Boundary Optimizing Network (BON) Marco Singh A. Pai 27 0 0 08 Jan 2018
Measuring the tendency of CNNs to Learn Surface Statistical Regularities Jason Jo Yoshua Bengio AAML 26 249 0 30 Nov 2017
Certifying Some Distributional Robustness with Principled Adversarial Training Aman Sinha Hongseok Namkoong Riccardo Volpi John C. Duchi OOD 58 855 0 29 Oct 2017
Towards Deep Learning Models Resistant to Adversarial Attacks A. Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 86 11,872 0 19 Jun 2017
Blocking Transferability of Adversarial Examples in Black-Box Learning Systems Hossein Hosseini Yize Chen Sreeram Kannan Baosen Zhang Radha Poovendran AAML 30 106 0 13 Mar 2017
Tactics of Adversarial Attack on Deep Reinforcement Learning Agents Yen-Chen Lin Zhang-Wei Hong Yuan-Hong Liao Meng-Li Shih Ming Liu Min Sun AAML 17 411 0 08 Mar 2017
On the (Statistical) Detection of Adversarial Examples Kathrin Grosse Praveen Manoharan Nicolas Papernot Michael Backes Patrick McDaniel AAML 39 709 0 21 Feb 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 296 3,113 0 04 Nov 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 310 2,892 0 15 Sep 2016