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Fine-grained Out-of-Distribution Detection with Mixup Outlier Exposure


Jun 07, 2021
Jingyang Zhang, Nathan Inkawhich, Yiran Chen, Hai Li


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Can Targeted Adversarial Examples Transfer When the Source and Target Models Have No Label Space Overlap?


Mar 17, 2021
Nathan Inkawhich, Kevin J Liang, Jingyang Zhang, Huanrui Yang, Hai Li, Yiran Chen


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The Untapped Potential of Off-the-Shelf Convolutional Neural Networks


Mar 17, 2021
Matthew Inkawhich, Nathan Inkawhich, Eric Davis, Hai Li, Yiran Chen

* 12 pages, 8 figures 

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DVERGE: Diversifying Vulnerabilities for Enhanced Robust Generation of Ensembles


Oct 18, 2020
Huanrui Yang, Jingyang Zhang, Hongliang Dong, Nathan Inkawhich, Andrew Gardner, Andrew Touchet, Wesley Wilkes, Heath Berry, Hai Li

* To be appeared in NeurIPS 2020 conference (Oral) 

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Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability


Apr 29, 2020
Nathan Inkawhich, Kevin J Liang, Binghui Wang, Matthew Inkawhich, Lawrence Carin, Yiran Chen


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Transferable Perturbations of Deep Feature Distributions


Apr 27, 2020
Nathan Inkawhich, Kevin J Liang, Lawrence Carin, Yiran Chen

* Published as a conference paper at ICLR 2020 

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Adversarial Attacks for Optical Flow-Based Action Recognition Classifiers


Nov 28, 2018
Nathan Inkawhich, Matthew Inkawhich, Yiran Chen, Hai Li


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