Toward Intrinsic Adversarial Robustness Through Probabilistic Training-Reference-Cited by-同舟云学术

Toward Intrinsic Adversarial Robustness Through Probabilistic Training

Published:2023 Issue: Volume:32 Page:3862-3872
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Dong Junhao¹^ORCID,Yang Lingxiao¹,Wang Yuan¹^ORCID,Xie Xiaohua¹^ORCID,Lai Jianhuang¹^ORCID

Affiliation:

1. School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9991910/10177878.pdf?arnumber=10177878

Reference67 articles.

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4. Power comparisons of Shapiro-Wilk, Kolmogorov-Smirnov, Lilliefors and Anderson-Darling tests;razali;Journal of Statistical Modeling and Analytics,2011

5. Geometry-aware instance-reweighted adversarial training;zhang;Proc Int Conf Learn Represent,2021

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