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Towards Understanding Adversarial Examples Systematically: Exploring
  Data Size, Task and Model Factors

Towards Understanding Adversarial Examples Systematically: Exploring Data Size, Task and Model Factors

28 February 2019
Ke Sun
Zhanxing Zhu
Zhouchen Lin
    AAML
ArXivPDFHTML

Papers citing "Towards Understanding Adversarial Examples Systematically: Exploring Data Size, Task and Model Factors"

4 / 4 papers shown
Title
Aug-NeRF: Training Stronger Neural Radiance Fields with Triple-Level
  Physically-Grounded Augmentations
Aug-NeRF: Training Stronger Neural Radiance Fields with Triple-Level Physically-Grounded Augmentations
Tianlong Chen
Peihao Wang
Zhiwen Fan
Zhangyang Wang
33
55
0
04 Jul 2022
Sparsity Winning Twice: Better Robust Generalization from More Efficient
  Training
Sparsity Winning Twice: Better Robust Generalization from More Efficient Training
Tianlong Chen
Zhenyu (Allen) Zhang
Pengju Wang
Santosh Balachandra
Haoyu Ma
Zehao Wang
Zhangyang Wang
OOD
AAML
77
46
0
20 Feb 2022
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
261
3,109
0
04 Nov 2016
Conditional Image Synthesis With Auxiliary Classifier GANs
Conditional Image Synthesis With Auxiliary Classifier GANs
Augustus Odena
C. Olah
Jonathon Shlens
GAN
238
3,190
0
30 Oct 2016
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