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Aaron Tuor
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2020 – today
- 2024
- [j3]Ján Drgona, Aaron Tuor, Draguna L. Vrabie:
Learning Constrained Parametric Differentiable Predictive Control Policies With Guarantees. IEEE Trans. Syst. Man Cybern. Syst. 54(6): 3596-3607 (2024) - 2022
- [c11]Ethan King, Ján Drgona, Aaron Tuor, Shrirang Abhyankar, Craig Bakker, Arnab Bhattacharya, Draguna L. Vrabie:
Koopman-based Differentiable Predictive Control for the Dynamics-Aware Economic Dispatch Problem. ACC 2022: 2194-2201 - [c10]Aowabin Rahman, Ján Drgona, Aaron Tuor, Jan Strube:
Neural Ordinary Differential Equations for Nonlinear System Identification. ACC 2022: 3979-3984 - [c9]Wenceslao Shaw-Cortez, Ján Drgona, Aaron Tuor, Mahantesh Halappanavar, Draguna L. Vrabie:
Differentiable Predictive Control with Safety Guarantees: A Control Barrier Function Approach. CDC 2022: 932-938 - [c8]Sayak Mukherjee, Ján Drgona, Aaron Tuor, Mahantesh Halappanavar, Draguna L. Vrabie:
Neural Lyapunov Differentiable Predictive Control. CDC 2022: 2097-2104 - [i23]Aowabin Rahman, Ján Drgona, Aaron Tuor, Jan Strube:
Neural Ordinary Differential Equations for Nonlinear System Identification. CoRR abs/2203.00120 (2022) - [i22]Ján Drgona, Sayak Mukherjee, Aaron Tuor, Mahantesh Halappanavar, Draguna L. Vrabie:
Learning Stochastic Parametric Differentiable Predictive Control Policies. CoRR abs/2203.01447 (2022) - [i21]Ethan King, Ján Drgona, Aaron Tuor, Shrirang Abhyankar, Craig Bakker, Arnab Bhattacharya, Draguna L. Vrabie:
Koopman-based Differentiable Predictive Control for the Dynamics-Aware Economic Dispatch Problem. CoRR abs/2203.08984 (2022) - [i20]Shrirang Abhyankar, Ján Drgona, Andrew August, Elliott Skomski, Aaron Tuor:
Neuro-physical dynamic load modeling using differentiable parametric optimization. CoRR abs/2203.10582 (2022) - [i19]Sayak Mukherjee, Ján Drgona, Aaron Tuor, Mahantesh Halappanavar, Draguna L. Vrabie:
Neural Lyapunov Differentiable Predictive Control. CoRR abs/2205.10728 (2022) - [i18]James Koch, Zhao Chen, Aaron Tuor, Ján Drgona, Draguna L. Vrabie:
Structural Inference of Networked Dynamical Systems with Universal Differential Equations. CoRR abs/2207.04962 (2022) - [i17]Wenceslao Shaw-Cortez, Ján Drgona, Aaron Tuor, Mahantesh Halappanavar, Draguna L. Vrabie:
Differentiable Predictive Control with Safety Guarantees: A Control Barrier Function Approach. CoRR abs/2208.02319 (2022) - [i16]Wenceslao Shaw-Cortez, Soumya Vasisht, Aaron Tuor, Ján Drgona, Draguna L. Vrabie:
Domain-aware Control-oriented Neural Models for Autonomous Underwater Vehicles. CoRR abs/2208.07333 (2022) - 2021
- [j2]Kyle B. Larson, Aaron Randall Tuor:
Deep Learning Classification of Cheatgrass Invasion in the Western United States Using Biophysical and Remote Sensing Data. Remote. Sens. 13(7): 1246 (2021) - [c7]Henry Kvinge, Zachary New, Nico Courts, Jung H. Lee, Lauren A. Phillips, Courtney D. Corley, Aaron Tuor, Andrew Avila, Nathan O. Hodas:
Fuzzy Simplicial Networks: A Topology-Inspired Model to Improve Task Generalization in Few-shot Learning. MetaDL@AAAI 2021: 77-89 - [c6]Elliott Skomski, Soumya Vasisht, Colby Wight, Aaron Tuor, Ján Drgona, Draguna L. Vrabie:
Constrained Block Nonlinear Neural Dynamical Models. ACC 2021: 3993-4000 - [c5]Elliott Skomski, Ján Drgona, Aaron Tuor:
Automating Discovery of Physics-Informed Neural State Space Models via Learning and Evolution. L4DC 2021: 980-991 - [i15]Elliott Skomski, Soumya Vasisht, Colby Wight, Aaron Tuor, Ján Drgona, Draguna L. Vrabie:
Constrained Block Nonlinear Neural Dynamical Models. CoRR abs/2101.01864 (2021) - [i14]Elliott Skomski, Aaron Tuor, Andrew Avila, Lauren A. Phillips, Zachary New, Henry Kvinge, Courtney D. Corley, Nathan O. Hodas:
Prototypical Region Proposal Networks for Few-Shot Localization and Classification. CoRR abs/2104.03496 (2021) - [i13]Ján Drgona, Aaron Tuor, Soumya Vasisht, Elliott Skomski, Draguna L. Vrabie:
Deep Learning Explicit Differentiable Predictive Control Laws for Buildings. CoRR abs/2107.11843 (2021) - 2020
- [c4]Loc Truong, Chace Jones, Brian Hutchinson, Andrew August, Brenda Praggastis, Robert Jasper, Nicole Nichols, Aaron Tuor:
Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers. CVPR Workshops 2020: 3422-3431 - [i12]Aaron Tuor, Ján Drgona, Draguna L. Vrabie:
Constrained Neural Ordinary Differential Equations with Stability Guarantees. CoRR abs/2004.10883 (2020) - [i11]Ján Drgona, Aaron Tuor, Draguna L. Vrabie:
Constrained Physics-Informed Deep Learning for Stable System Identification and Control of Unknown Linear Systems. CoRR abs/2004.11184 (2020) - [i10]Loc Truong, Chace Jones, Brian Hutchinson, Andrew August, Brenda Praggastis, Robert Jasper, Nicole Nichols, Aaron Tuor:
Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers. CoRR abs/2004.11514 (2020) - [i9]Henry Kvinge, Zachary New, Nico Courts, Jung H. Lee, Lauren A. Phillips, Courtney D. Corley, Aaron Tuor, Andrew Avila, Nathan O. Hodas:
Fuzzy Simplicial Networks: A Topology-Inspired Model to Improve Task Generalization in Few-shot Learning. CoRR abs/2009.11253 (2020) - [i8]Ján Drgona, Karol Kis, Aaron Tuor, Draguna L. Vrabie, Martin Klauco:
Differentiable Predictive Control: An MPC Alternative for Unknown Nonlinear Systems using Constrained Deep Learning. CoRR abs/2011.03699 (2020) - [i7]Ján Drgona, Aaron Randall Tuor, Vikas Chandan, Draguna L. Vrabie:
Physics-constrained Deep Learning of Multi-zone Building Thermal Dynamics. CoRR abs/2011.05987 (2020) - [i6]Ján Drgona, Elliott Skomski, Soumya Vasisht, Aaron Tuor, Draguna L. Vrabie:
Spectral Analysis and Stability of Deep Neural Dynamics. CoRR abs/2011.13492 (2020) - [i5]Elliott Skomski, Ján Drgona, Aaron Tuor:
Physics-Informed Neural State Space Models via Learning and Evolution. CoRR abs/2011.13497 (2020)
2010 – 2019
- 2019
- [i4]Aaron Tuor, Fnu Anubhav, Lauren Charles:
Multiple Document Representations from News Alerts for Automated Bio-surveillance Event Detection. CoRR abs/1902.06231 (2019) - 2018
- [j1]Richard Olney, Aaron Tuor, Filip Jagodzinski, Brian Hutchinson:
A systematic exploration of ΔΔG cutoff ranges in machine learning models for protein mutation stability prediction. J. Bioinform. Comput. Biol. 16(5): 1840022:1-1840022:19 (2018) - [c3]Aaron Randall Tuor, Ryan Baerwolf, Nicolas Knowles, Brian Hutchinson, Nicole Nichols, Robert Jasper:
Recurrent Neural Network Language Models for Open Vocabulary Event-Level Cyber Anomaly Detection. AAAI Workshops 2018: 285-293 - [i3]Andy Brown, Aaron Tuor, Brian Hutchinson, Nicole Nichols:
Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection. CoRR abs/1803.04967 (2018) - 2017
- [c2]Aaron Tuor, Samuel Kaplan, Brian Hutchinson, Nicole Nichols, Sean Robinson:
Predicting User Roles from Computer Logs Using Recurrent Neural Networks. AAAI 2017: 4993-4994 - [c1]Aaron Tuor, Samuel Kaplan, Brian Hutchinson, Nicole Nichols, Sean Robinson:
Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams. AAAI Workshops 2017 - [i2]Aaron Tuor, Samuel Kaplan, Brian Hutchinson, Nicole Nichols, Sean Robinson:
Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams. CoRR abs/1710.00811 (2017) - [i1]Aaron Tuor, Ryan Baerwolf, Nicolas Knowles, Brian Hutchinson, Nicole Nichols, Robert Jasper:
Recurrent Neural Network Language Models for Open Vocabulary Event-Level Cyber Anomaly Detection. CoRR abs/1712.00557 (2017)
Coauthor Index
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last updated on 2024-10-07 21:22 CEST by the dblp team
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