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RoBIC: A benchmark suite for assessing classifiers robustness

RoBIC: A benchmark suite for assessing classifiers robustness

10 February 2021
Thibault Maho
Benoît Bonnet
Teddy Furon
Erwan Le Merrer
    AAML
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Papers citing "RoBIC: A benchmark suite for assessing classifiers robustness"

3 / 3 papers shown
Title
Selecting Models based on the Risk of Damage Caused by Adversarial
  Attacks
Selecting Models based on the Risk of Damage Caused by Adversarial Attacks
Jona Klemenc
Holger Trittenbach
AAML
24
1
0
28 Jan 2023
RobustBench: a standardized adversarial robustness benchmark
RobustBench: a standardized adversarial robustness benchmark
Francesco Croce
Maksym Andriushchenko
Vikash Sehwag
Edoardo Debenedetti
Nicolas Flammarion
M. Chiang
Prateek Mittal
Matthias Hein
VLM
234
677
0
19 Oct 2020
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
287
5,837
0
08 Jul 2016
1