Fortified Networks: Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations

7 April 2018

Papers citing "Fortified Networks: Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations"

23 / 23 papers shown

Title
A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies Zhuang Qian Kaizhu Huang Qiufeng Wang Xu-Yao Zhang OOD AAML ObjD 49 71 0 26 Mar 2022
Robust Upper Bounds for Adversarial Training Dimitris Bertsimas Xavier Boix Kimberly Villalobos Carballo D. Hertog AAML 35 0 0 17 Dec 2021
Holistic Deep Learning Dimitris Bertsimas Kimberly Villalobos Carballo L. Boussioux M. Li Alex Paskov I. Paskov 27 1 0 29 Oct 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 32 65 0 09 Apr 2021
FADER: Fast Adversarial Example Rejection Francesco Crecchi Marco Melis Angelo Sotgiu D. Bacciu Battista Biggio AAML 14 15 0 18 Oct 2020
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective G. R. Machado Eugênio Silva R. Goldschmidt AAML 24 155 0 08 Sep 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 25 73 0 07 Aug 2020
TEAM: We Need More Powerful Adversarial Examples for DNNs Yaguan Qian Xi-Ming Zhang Bin Wang Wei Li Zhaoquan Gu Haijiang Wang Wassim Swaileh AAML 27 0 0 31 Jul 2020
Can Attention Masks Improve Adversarial Robustness? Pratik Vaishnavi Tianji Cong Kevin Eykholt A. Prakash Amir Rahmati AAML 11 12 0 27 Nov 2019
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 13 103 0 13 Nov 2019
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations Alex Lamb Jonathan Binas Anirudh Goyal Sandeep Subramanian Ioannis Mitliagkas Denis Kazakov Yoshua Bengio Michael C. Mozer OOD 16 3 0 26 May 2019
Weight Map Layer for Noise and Adversarial Attack Robustness Mohammed Amer Tomás Maul 12 4 0 02 May 2019
ZK-GanDef: A GAN based Zero Knowledge Adversarial Training Defense for Neural Networks Guanxiong Liu Issa M. Khalil Abdallah Khreishah AAML 16 18 0 17 Apr 2019
GanDef: A GAN based Adversarial Training Defense for Neural Network Classifier Guanxiong Liu Issa M. Khalil Abdallah Khreishah GAN AAML 27 19 0 06 Mar 2019
A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations Saeid Asgari Taghanaki Kumar Abhishek Shekoofeh Azizi Ghassan Hamarneh AAML 31 40 0 03 Mar 2019
Disentangling Adversarial Robustness and Generalization David Stutz Matthias Hein Bernt Schiele AAML OOD 191 273 0 03 Dec 2018
Adversarial Gain Peter Henderson Koustuv Sinha Nan Rosemary Ke Joelle Pineau AAML 16 0 0 04 Nov 2018
Adversarial Examples - A Complete Characterisation of the Phenomenon A. Serban E. Poll Joost Visser SILM AAML 25 49 0 02 Oct 2018
Motivating the Rules of the Game for Adversarial Example Research Justin Gilmer Ryan P. Adams Ian Goodfellow David G. Andersen George E. Dahl AAML 50 226 0 18 Jul 2018
Robustifying Models Against Adversarial Attacks by Langevin Dynamics Vignesh Srinivasan Arturo Marbán K. Müller Wojciech Samek Shinichi Nakajima AAML 17 9 0 30 May 2018
Deep Active Learning for Anomaly Detection Tiago Pimentel Marianne Monteiro Adriano Veloso N. Ziviani 24 39 0 23 May 2018
Robust Conditional Generative Adversarial Networks Grigorios G. Chrysos Jean Kossaifi S. Zafeiriou GAN 27 30 0 22 May 2018
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 261 3,110 0 04 Nov 2016