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Understanding (Non-)Robust Feature Disentanglement and the Relationship
  Between Low- and High-Dimensional Adversarial Attacks

Understanding (Non-)Robust Feature Disentanglement and the Relationship Between Low- and High-Dimensional Adversarial Attacks

4 April 2020
Zuowen Wang
Leo Horne
    AAML
ArXivPDFHTML

Papers citing "Understanding (Non-)Robust Feature Disentanglement and the Relationship Between Low- and High-Dimensional Adversarial Attacks"

4 / 4 papers shown
Title
Evaluating and Understanding the Robustness of Adversarial Logit Pairing
Evaluating and Understanding the Robustness of Adversarial Logit Pairing
Logan Engstrom
Andrew Ilyas
Anish Athalye
AAML
29
141
0
26 Jul 2018
Evasion Attacks against Machine Learning at Test Time
Evasion Attacks against Machine Learning at Test Time
Battista Biggio
Igino Corona
Davide Maiorca
B. Nelson
Nedim Srndic
Pavel Laskov
Giorgio Giacinto
Fabio Roli
AAML
63
2,140
0
21 Aug 2017
Spatial Transformer Networks
Spatial Transformer Networks
Max Jaderberg
Karen Simonyan
Andrew Zisserman
Koray Kavukcuoglu
236
7,361
0
05 Jun 2015
Intriguing properties of neural networks
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
45
14,831
1
21 Dec 2013
1