{"title":"EnResNet: ResNets Ensemble via the Feynman-Kac Formalism for Adversarial Defense and Beyond","authors":"Bao Wang, Binjie Yuan, Zuoqiang Shi, S. Osher","doi":"10.1137/19m1265302","DOIUrl":null,"url":null,"abstract":"Empirical adversarial risk minimization is a widely used mathematical framework to robustly train deep neural nets that are resistant to adversarial attacks. However, both natural and robust accura...","PeriodicalId":74797,"journal":{"name":"SIAM journal on mathematics of data science","volume":"96 1","pages":"559-582"},"PeriodicalIF":1.9000,"publicationDate":"2020-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIAM journal on mathematics of data science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1137/19m1265302","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 8
Abstract
Empirical adversarial risk minimization is a widely used mathematical framework to robustly train deep neural nets that are resistant to adversarial attacks. However, both natural and robust accura...
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