First-order Adversarial Vulnerability of Neural Networks and Input Dimension

5 February 2018

Papers citing "First-order Adversarial Vulnerability of Neural Networks and Input Dimension"

7 / 7 papers shown

Title
A Learning Paradigm for Interpretable Gradients Felipe Figueroa Hanwei Zhang R. Sicre Yannis Avrithis Stéphane Ayache FAtt 18 0 0 23 Apr 2024
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 22 65 0 09 Apr 2021
Investigating Vulnerability to Adversarial Examples on Multimodal Data Fusion in Deep Learning Youngjoon Yu Hong Joo Lee Byeong Cheon Kim Jung Uk Kim Yong Man Ro AAML 28 18 0 22 May 2020
Scaleable input gradient regularization for adversarial robustness Chris Finlay Adam M. Oberman AAML 8 77 0 27 May 2019
A Kernel Perspective for Regularizing Deep Neural Networks A. Bietti Grégoire Mialon Dexiong Chen Julien Mairal 11 15 0 30 Sep 2018
Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks Ambra Demontis Marco Melis Maura Pintor Matthew Jagielski Battista Biggio Alina Oprea Cristina Nita-Rotaru Fabio Roli SILM AAML 11 11 0 08 Sep 2018
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 23 1,388 0 08 Dec 2017