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Improving Out-of-Distribution Detection via Epistemic Uncertainty Adversarial Training


Sep 09, 2022
Derek Everett, Andre T. Nguyen, Luke E. Richards, Edward Raff

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* 8 pages, 5 figures 

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Out of Distribution Data Detection Using Dropout Bayesian Neural Networks


Feb 18, 2022
Andre T. Nguyen, Fred Lu, Gary Lopez Munoz, Edward Raff, Charles Nicholas, James Holt

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Leveraging Uncertainty for Improved Static Malware Detection Under Extreme False Positive Constraints


Aug 09, 2021
Andre T. Nguyen, Edward Raff, Charles Nicholas, James Holt

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Practical Cross-modal Manifold Alignment for Grounded Language


Sep 01, 2020
Andre T. Nguyen, Luke E. Richards, Gaoussou Youssouf Kebe, Edward Raff, Kasra Darvish, Frank Ferraro, Cynthia Matuszek

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Towards the Use of Neural Networks for Influenza Prediction at Multiple Spatial Resolutions


Nov 13, 2019
Emily L. Aiken, Andre T. Nguyen, Mauricio Santillana

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* Machine Learning for Health (ML4H) at NeurIPS 2019 - Extended Abstract; Added Footer 

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Robust Design of Deep Neural Networks against Adversarial Attacks based on Lyapunov Theory


Nov 12, 2019
Arash Rahnama, Andre T. Nguyen, Edward Raff

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Would a File by Any Other Name Seem as Malicious?


Oct 10, 2019
Andre T. Nguyen, Edward Raff, Aaron Sant-Miller

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Heterogeneous Relational Kernel Learning


Aug 24, 2019
Andre T. Nguyen, Edward Raff

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* MileTS '19: 5th KDD Workshop on Mining and Learning from Time Series 

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Connecting Lyapunov Control Theory to Adversarial Attacks


Jul 17, 2019
Arash Rahnama, Andre T. Nguyen, Edward Raff

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* 8 pages, 3 figures, AdvML'19: Workshop on Adversarial Learning Methods for Machine Learning and Data Mining at KDD 

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