Aaron Tuor - RankMe

36 papers A* 1C 3Journal 26Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Data Center Chiller Plant Optimization via Mixed-Integer Nonlinear Differentiable Predictive Control. CoRR Ján Boldocký, Cary Faulkner, Elad Michael, Martin Gulan, Aaron Tuor, Ján Drgona
2025	J	`jnl`	Homotopy-Guided Self-Supervised Learning of Parametric Solutions for AC Optimal Power Flow. CoRR Shimiao Li, Aaron Tuor, Draguna L. Vrabie, Larry T. Pileggi, Ján Drgona
2024	J	`jnl`	Learning Constrained Parametric Differentiable Predictive Control Policies With Guarantees. IEEE Trans. Syst. Man Cybern. Syst. Ján Drgona, Aaron Tuor, Draguna L. Vrabie
2022	—	`conf`	Differentiable Predictive Control with Safety Guarantees: A Control Barrier Function Approach. CDC Wenceslao Shaw-Cortez, Ján Drgona, Aaron Tuor, Mahantesh Halappanavar, Draguna L. Vrabie
2022	J	`jnl`	Differentiable Predictive Control with Safety Guarantees: A Control Barrier Function Approach. CoRR Wenceslao Shaw-Cortez, Ján Drgona, Aaron Tuor, Mahantesh Halappanavar, Draguna L. Vrabie
2022	J	`jnl`	Domain-aware Control-oriented Neural Models for Autonomous Underwater Vehicles. CoRR Wenceslao Shaw-Cortez, Soumya Vasisht, Aaron Tuor, Ján Drgona, Draguna L. Vrabie
2022	C	`conf`	Koopman-based Differentiable Predictive Control for the Dynamics-Aware Economic Dispatch Problem. ACC Ethan King, Ján Drgona, Aaron Tuor, Shrirang Abhyankar, Craig Bakker, Arnab Bhattacharya, Draguna L. Vrabie
2022	J	`jnl`	Koopman-based Differentiable Predictive Control for the Dynamics-Aware Economic Dispatch Problem. CoRR Ethan King, Ján Drgona, Aaron Tuor, Shrirang Abhyankar, Craig Bakker, Arnab Bhattacharya, Draguna L. Vrabie
2022	J	`jnl`	Learning Stochastic Parametric Differentiable Predictive Control Policies. CoRR Ján Drgona, Sayak Mukherjee, Aaron Tuor, Mahantesh Halappanavar, Draguna L. Vrabie
2022	—	`conf`	Neural Lyapunov Differentiable Predictive Control. CDC Sayak Mukherjee, Ján Drgona, Aaron Tuor, Mahantesh Halappanavar, Draguna L. Vrabie
2022	J	`jnl`	Neural Lyapunov Differentiable Predictive Control. CoRR Sayak Mukherjee, Ján Drgona, Aaron Tuor, Mahantesh Halappanavar, Draguna L. Vrabie
2022	C	`conf`	Neural Ordinary Differential Equations for Nonlinear System Identification. ACC Aowabin Rahman, Ján Drgona, Aaron Tuor, Jan Strube
2022	J	`jnl`	Neural Ordinary Differential Equations for Nonlinear System Identification. CoRR Aowabin Rahman, Ján Drgona, Aaron Tuor, Jan Strube
2022	J	`jnl`	Neuro-physical dynamic load modeling using differentiable parametric optimization. CoRR Shrirang Abhyankar, Ján Drgona, Andrew August, Elliott Skomski, Aaron Tuor
2022	J	`jnl`	Structural Inference of Networked Dynamical Systems with Universal Differential Equations. CoRR James Koch, Zhao Chen, Aaron Tuor, Ján Drgona, Draguna L. Vrabie
2021	—	`conf`	Automating Discovery of Physics-Informed Neural State Space Models via Learning and Evolution. L4DC Elliott Skomski, Ján Drgona, Aaron Tuor
2021	C	`conf`	Constrained Block Nonlinear Neural Dynamical Models. ACC Elliott Skomski, Soumya Vasisht, Colby Wight, Aaron Tuor, Ján Drgona, Draguna L. Vrabie
2021	J	`jnl`	Constrained Block Nonlinear Neural Dynamical Models. CoRR Elliott Skomski, Soumya Vasisht, Colby Wight, Aaron Tuor, Ján Drgona, Draguna L. Vrabie
2021	J	`jnl`	Deep Learning Explicit Differentiable Predictive Control Laws for Buildings. CoRR Ján Drgona, Aaron Tuor, Soumya Vasisht, Elliott Skomski, Draguna L. Vrabie
2021	—	`conf`	Fuzzy Simplicial Networks: A Topology-Inspired Model to Improve Task Generalization in Few-shot Learning. MetaDL@AAAI Henry Kvinge, Zachary New, Nico Courts, Jung H. Lee, Lauren A. Phillips, Courtney D. Corley, Aaron Tuor, Andrew Avila, Nathan O. Hodas
2021	J	`jnl`	Prototypical Region Proposal Networks for Few-Shot Localization and Classification. CoRR Elliott Skomski, Aaron Tuor, Andrew Avila, Lauren A. Phillips, Zachary New, Henry Kvinge, Courtney D. Corley, Nathan O. Hodas
2020	J	`jnl`	Constrained Neural Ordinary Differential Equations with Stability Guarantees. CoRR Aaron Tuor, Ján Drgona, Draguna L. Vrabie
2020	J	`jnl`	Constrained Physics-Informed Deep Learning for Stable System Identification and Control of Unknown Linear Systems. CoRR Ján Drgona, Aaron Tuor, Draguna L. Vrabie
2020	J	`jnl`	Differentiable Predictive Control: An MPC Alternative for Unknown Nonlinear Systems using Constrained Deep Learning. CoRR Ján Drgona, Karol Kis, Aaron Tuor, Draguna L. Vrabie, Martin Klauco
2020	J	`jnl`	Fuzzy Simplicial Networks: A Topology-Inspired Model to Improve Task Generalization in Few-shot Learning. CoRR Henry Kvinge, Zachary New, Nico Courts, Jung H. Lee, Lauren A. Phillips, Courtney D. Corley, Aaron Tuor, Andrew Avila, Nathan O. Hodas
2020	J	`jnl`	Physics-Informed Neural State Space Models via Learning and Evolution. CoRR Elliott Skomski, Ján Drgona, Aaron Tuor
2020	J	`jnl`	Spectral Analysis and Stability of Deep Neural Dynamics. CoRR Ján Drgona, Elliott Skomski, Soumya Vasisht, Aaron Tuor, Draguna L. Vrabie
2020	—	`conf`	Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers. CVPR Workshops Loc Truong, Chace Jones, Brian Hutchinson, Andrew August, Brenda Praggastis, Robert Jasper, Nicole Nichols, Aaron Tuor
2020	J	`jnl`	Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers. CoRR Loc Truong, Chace Jones, Brian Hutchinson, Andrew August, Brenda Praggastis, Robert Jasper, Nicole Nichols, Aaron Tuor
2019	J	`jnl`	Multiple Document Representations from News Alerts for Automated Bio-surveillance Event Detection. CoRR Aaron Tuor, Fnu Anubhav, Lauren E. Charles
2018	J	`jnl`	A systematic exploration of ΔΔG cutoff ranges in machine learning models for protein mutation stability prediction. J. Bioinform. Comput. Biol. Richard Olney, Aaron Tuor, Filip Jagodzinski, Brian Hutchinson
2018	J	`jnl`	Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection. CoRR Andy Brown, Aaron Tuor, Brian Hutchinson, Nicole Nichols
2017	—	`conf`	Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams. AAAI Workshops Aaron Tuor, Samuel Kaplan, Brian Hutchinson, Nicole Nichols, Sean Robinson
2017	J	`jnl`	Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams. CoRR Aaron Tuor, Samuel Kaplan, Brian Hutchinson, Nicole Nichols, Sean Robinson
2017	A*	`conf`	Predicting User Roles from Computer Logs Using Recurrent Neural Networks. AAAI Aaron Tuor, Samuel Kaplan, Brian Hutchinson, Nicole Nichols, Sean Robinson
2017	J	`jnl`	Recurrent Neural Network Language Models for Open Vocabulary Event-Level Cyber Anomaly Detection. CoRR Aaron Tuor, Ryan Baerwolf, Nicolas Knowles, Brian Hutchinson, Nicole Nichols, Robert Jasper