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Deep Learning Explicit Differentiable Predictive Control Laws for Buildings


Jul 25, 2021
Jan Drgona, Aaron Tuor, Soumya Vasisht, Elliott Skomski, Draguna Vrabie


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Prototypical Region Proposal Networks for Few-Shot Localization and Classification


Apr 08, 2021
Elliott Skomski, Aaron Tuor, Andrew Avila, Lauren Phillips, Zachary New, Henry Kvinge, Courtney D. Corley, Nathan Hodas

* 9 pages, 1 figure. Submitted to 4th Workshop on Meta-Learning at NeurIPS 2020 

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Constrained Block Nonlinear Neural Dynamical Models


Jan 06, 2021
Elliott Skomski, Soumya Vasisht, Colby Wight, Aaron Tuor, Jan Drgona, Draguna Vrabie

* 10 pages. Submitted to American Control Conference ACC 2020. Under review 

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Physics-Informed Neural State Space Models via Learning and Evolution


Nov 26, 2020
Elliott Skomski, Jan Drgona, Aaron Tuor

* Submitted to 3rd Annual Learning for Dynamics & Control Conference. 9 pages. 4 figures 

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Spectral Analysis and Stability of Deep Neural Dynamics


Nov 26, 2020
Jan Drgona, Elliott Skomski, Soumya Vasisht, Aaron Tuor, Draguna Vrabie

* Submitted to 3rd Annual Learning for Dynamics & Control Conference. 10 pages. 4 figures 

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Fuzzy Simplicial Networks: A Topology-Inspired Model to Improve Task Generalization in Few-shot Learning


Sep 23, 2020
Henry Kvinge, Zachary New, Nico Courts, Jung H. Lee, Lauren A. Phillips, Courtney D. Corley, Aaron Tuor, Andrew Avila, Nathan O. Hodas

* 17 pages 

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Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers


Apr 24, 2020
Loc Truong, Chace Jones, Brian Hutchinson, Andrew August, Brenda Praggastis, Robert Jasper, Nicole Nichols, Aaron Tuor


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Constrained Physics-Informed Deep Learning for Stable System Identification and Control of Unknown Linear Systems


Apr 24, 2020
Jan Drgona, Aaron Tuor, Draguna Vrabie

* 11 pages 

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Constrained Neural Ordinary Differential Equations with Stability Guarantees


Apr 22, 2020
Aaron Tuor, Jan Drgona, Draguna Vrabie

* 4 pages, Appendix 

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Multiple Document Representations from News Alerts for Automated Bio-surveillance Event Detection


Feb 17, 2019
Aaron Tuor, Fnu Anubhav, Lauren Charles

* Presented at the 5th Pacific Northwest Regional NLP Workshop: NW-NLP 2018 

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Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection


Mar 13, 2018
Andy Brown, Aaron Tuor, Brian Hutchinson, Nicole Nichols

* Submitted to the First Workshop On Machine Learning for Computer Systems, ACM HPDC 2018 

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Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams


Dec 15, 2017
Aaron Tuor, Samuel Kaplan, Brian Hutchinson, Nicole Nichols, Sean Robinson

* Proceedings of AI for Cyber Security Workshop at AAAI 2017 

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Recurrent Neural Network Language Models for Open Vocabulary Event-Level Cyber Anomaly Detection


Dec 02, 2017
Aaron Tuor, Ryan Baerwolf, Nicolas Knowles, Brian Hutchinson, Nicole Nichols, Rob Jasper

* 8 pages, To appear in proceedings of AAAI-2018 Artificial Intelligence in Cyber Security Workshop 

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