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Improved Adversarial Robustness via Logit Regularization Methods

Improved Adversarial Robustness via Logit Regularization Methods

10 June 2019
Cecilia Summers
M. Dinneen
    AAML
ArXivPDFHTML

Papers citing "Improved Adversarial Robustness via Logit Regularization Methods"

4 / 4 papers shown
Title
Standard-Deviation-Inspired Regularization for Improving Adversarial Robustness
Standard-Deviation-Inspired Regularization for Improving Adversarial Robustness
Olukorede Fakorede
Modeste Atsague
Jin Tian
AAML
37
0
0
31 Dec 2024
Understanding the Logit Distributions of Adversarially-Trained Deep
  Neural Networks
Understanding the Logit Distributions of Adversarially-Trained Deep Neural Networks
Landan Seguin
A. Ndirango
Neeli Mishra
SueYeon Chung
Tyler Lee
OOD
25
2
0
26 Aug 2021
How to Certify Machine Learning Based Safety-critical Systems? A
  Systematic Literature Review
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
25
65
0
26 Jul 2021
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
287
5,835
0
08 Jul 2016
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