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Rethinking Uncertainty in Deep Learning: Whether and How it Improves
  Robustness

Rethinking Uncertainty in Deep Learning: Whether and How it Improves Robustness

27 November 2020
Yilun Jin
Lixin Fan
Kam Woh Ng
Ce Ju
Qiang Yang
    AAML
    OOD
ArXivPDFHTML

Papers citing "Rethinking Uncertainty in Deep Learning: Whether and How it Improves Robustness"

2 / 2 papers shown
Title
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
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
293
5,842
0
08 Jul 2016
1