Ján Drgona - RankMe

79 papers A* 3A 1C 6Journal 56Unranked 13

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
2026	J	`jnl`	Koopman-BoxQP: Solving Large-Scale NMPC at kHz Rates. CoRR Liang Wu, Wallace Tan Gian Yion, Richard D. Braatz, Ján Drgona
2026	J	`jnl`	L2O-CCG: Adversarial Learning with Set Generalization for Adaptive Robust Optimization. CoRR Zhiyi Zhou, Ján Drgona, Yury Dvorkin
2026	J	`jnl`	Least-Squares Multi-Step Koopman Operator Learning for Model Predictive Control. CoRR Liang Wu, Wallace Tan Gian Yion, Leqi Zhou, Richard D. Braatz, Ján Drgona
2026	J	`jnl`	SCORE: Statistical Certification of Regions of Attraction via Extreme Value Theory. CoRR Pietro Zanotta, Panos Stinis, Ján Drgona
2026	J	`jnl`	Time-Certified and Efficient NMPC via Koopman Operator. CoRR Liang Wu, Yunhong Che, Bo Yang, Kangyu Lin, Ján Drgona
2026	J	`jnl`	πMPC: A Parallel-in-horizon and Construction-free NMPC Solver. CoRR Liang Wu, Bo Yang, Xu Yang, Yilin Mo, Yang Shi, Ján Drgona
2026	J	`jnl`	∂CBDs: Differentiable Causal Block Diagrams. CoRR Thomas Beckers, Ján Drgona, Truong X. Nghiem
2025	J	`jnl`	A Method for Learning to Solve Parametric Bilevel Optimization with Coupling Constraints. CoRR James Kotary, Himanshu Sharma, Ethan King, Draguna L. Vrabie, Ferdinando Fioretto, Ján Drgona
2025	J	`jnl`	A Time-Certified Predictor-Corrector IPM Algorithm for Box-QP. IEEE Control. Syst. Lett. Liang Wu, Yunhong Che, Richard D. Braatz, Ján Drgona
2025	J	`jnl`	Accelerating Underground Pumped Hydro Energy Storage Scheduling with Decision-Focused Learning. CoRR Honghui Zheng, Pietro Favaro, Yury Dvorkin, Ján Drgona
2025	J	`jnl`	E-PINNs: Epistemic Physics-Informed Neural Networks. CoRR Ashish S. Nair, Bruno Jacob, Amanda A. Howard, Ján Drgona, Panos Stinis
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
2025	—	`conf`	Learning Neural Differential Algebraic Equations via Operator Splitting. CDC James Koch, Madelyn Shapiro, Himanshu Sharma, Draguna L. Vrabie, Ján Drgona
2025	J	`jnl`	Learning to Control PDEs with Differentiable Predictive Control and Time-Integrated Neural Operators. CoRR Dibakar Roy Sarkar, Ján Drgona, Somdatta Goswami
2025	J	`jnl`	Learning to Solve Parametric Mixed-Integer Optimal Control Problems via Differentiable Predictive Control. CoRR Ján Boldocký, Shahriar Dadras Javan, Martin Gulan, Martin Mönnigmann, Ján Drgona
2025	J	`jnl`	Physics-informed machine learning for building performance simulation-A review of a nascent field. CoRR Zixin Jiang, Xuezheng Wang, Han Li, Tianzhen Hong, Fengqi You, Ján Drgona, Draguna L. Vrabie, Bing Dong
2025	J	`jnl`	Safe Physics-Informed Machine Learning for Dynamics and Control. CoRR Ján Drgona, Truong X. Nghiem, Thomas Beckers, Mahyar Fazlyab, Enrique Mallada, Colin N. Jones, Draguna L. Vrabie, Steven L. Brunton, Rolf Findeisen
2025	C	`conf`	Safe Physics-informed Machine Learning for Dynamics and Control. ACC Ján Drgona, Truong X. Nghiem, Thomas Beckers, Mahyar Fazlyab, Enrique Mallada, Colin N. Jones, Draguna L. Vrabie, Steven L. Brunton, Rolf Findeisen
2025	J	`jnl`	Zero-Shot Function Encoder-Based Differentiable Predictive Control. CoRR Hassan Iqbal, Xingjian Li, Tyler Ingebrand, Adam J. Thorpe, Krishna Kumar, Ufuk Topcu, Ján Drgona
2025	J	`jnl`	Zero-Shot Transferable Solution Method for Parametric Optimal Control Problems. CoRR Xingjian Li, Kelvin Kan, Deepanshu Verma, Krishna Kumar, Stanley J. Osher, Ján Drgona
2024	J	`jnl`	Differentiable Predictive Control for Large-Scale Urban Road Networks. CoRR Renukanandan Tumu, Wenceslao Shaw-Cortez, Ján Drgona, Draguna L. Vrabie, Sonja Glavaski
2024	J	`jnl`	Differentiable Predictive Control for Robotics: A Data-Driven Predictive Safety Filter Approach. CoRR John Viljoen, Wenceslao Shaw-Cortez, Ján Drgona, Sebastian East, Masayoshi Tomizuka, Draguna L. Vrabie
2024	J	`jnl`	Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory. Trans. Mach. Learn. Res. Karthik Somayaji N. S., Yu Wang, Malachi Schram, Ján Drgona, Mahantesh M. Halappanavar, Frank Liu, Peng Li
2024	A	`conf`	Finding MIDDLE Ground: Scalable and Secure Distributed Learning. CIKM Marco Bornstein, Nawaf Nazir, Ján Drgona, Soumya Kundu, Veronica Adetola
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
2024	J	`jnl`	Learning to Optimize for Mixed-Integer Non-linear Programming. CoRR Bo Tang, Elias B. Khalil, Ján Drgona
2024	J	`jnl`	Metric Learning to Accelerate Convergence of Operator Splitting Methods for Differentiable Parametric Programming. CoRR Ethan King, James Kotary, Ferdinando Fioretto, Ján Drgona
2024	—	`conf`	Metric Learning to Accelerate Convergence of Operator Splitting Methods. CDC Ethan King, James Kotary, Ferdinando Fioretto, Ján Drgona
2024	J	`jnl`	Neural Differential Algebraic Equations. CoRR James Koch, Madelyn Shapiro, Himanshu Sharma, Draguna L. Vrabie, Ján Drgona
2024	A*	`conf`	Semi-supervised Learning of Dynamical Systems with Neural Ordinary Differential Equations: A Teacher-Student Model Approach. AAAI Yu Wang, Yuxuan Yin, Karthik Somayaji N. S., Ján Drgona, Malachi Schram, Mahantesh Halappanavar, Frank Liu, Peng Li
2023	A*	`conf`	AutoNF: Automated Architecture Optimization of Normalizing Flows with Unconstrained Continuous Relaxation Admitting Optimal Discrete Solution. AAAI Yu Wang, Ján Drgona, Jiaxin Zhang, Karthik Somayaji Nanjangud Suryanarayana, Malachi Schram, Frank Liu, Peng Li
2023	J	`jnl`	Constructing Neural Network Based Models for Simulating Dynamical Systems. ACM Comput. Surv. Christian Møldrup Legaard, Thomas Schranz, Gerald Schweiger, Ján Drgona, Basak Falay, Cláudio Gomes, Alexandros Iosifidis, Mahdi Abkar, Peter Gorm Larsen
2023	C	`conf`	Data-Driven Control: Theory and Applications. ACC Damoon Soudbakhsh, Anuradha M. Annaswamy, Yan Wang, Steven L. Brunton, Joseph E. Gaudio, Heather S. Hussain, Draguna L. Vrabie, Ján Drgona, Dimitar P. Filev
2023	J	`jnl`	Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory. CoRR Karthik Somayaji N. S., Yu Wang, Malachi Schram, Ján Drgona, Mahantesh Halappanavar, Frank Liu, Peng Li
2023	C	`conf`	Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems. ACC Truong X. Nghiem, Ján Drgona, Colin N. Jones, Zoltán Nagy, Roland Schwan, Biswadip Dey, Ankush Chakrabarty, Stefano Di Cairano, Joel A. Paulson, Andrea Carron, Melanie N. Zeilinger, Wenceslao Shaw-Cortez, Draguna L. Vrabie
2023	J	`jnl`	Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems. CoRR Truong X. Nghiem, Ján Drgona, Colin N. Jones, Zoltán Nagy, Roland Schwan, Biswadip Dey, Ankush Chakrabarty, Stefano Di Cairano, Joel A. Paulson, Andrea Carron, Melanie N. Zeilinger, Wenceslao Shaw-Cortez, Draguna L. Vrabie
2023	—	`conf`	Power Grid Behavioral Patterns and Risks of Generalization in Applied Machine Learning. e-Energy (Companion) Shimiao Li, Ján Drgona, Shrirang Abhyankar, Larry T. Pileggi
2023	J	`jnl`	Power Grid Behavioral Patterns and Risks of Generalization in Applied Machine Learning. CoRR Shimiao Li, Ján Drgona, Shrirang Abhyankar, Larry T. Pileggi
2023	J	`jnl`	Robust Differentiable Predictive Control with Safety Guarantees: A Predictive Safety Filter Approach. CoRR Wenceslao Shaw-Cortez, Ján Drgona, Draguna L. Vrabie, Mahantesh Halappanavar
2023	J	`jnl`	Semi-Supervised Learning of Dynamical Systems with Neural Ordinary Differential Equations: A Teacher-Student Model Approach. CoRR Yu Wang, Yuxuan Yin, Karthik Somayaji Nanjangud Suryanarayana, Ján Drgona, Malachi Schram, Mahantesh Halappanavar, Frank Liu, Peng Li
2022	—	`conf`	Data-driven Stabilization of Discrete-time Control-affine Nonlinear Systems: A Koopman Operator Approach. ECC Subhrajit Sinha, Sai Pushpak Nandanoori, Ján Drgona, Draguna L. Vrabie
2022	J	`jnl`	Data-driven Stabilization of Discrete-time Control-affine Nonlinear Systems: A Koopman Operator Approach. CoRR Subhrajit Sinha, Sai Pushpak Nandanoori, Ján Drgona, 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	J	`jnl`	Machine Learning for Smart and Energy-Efficient Buildings. CoRR Hari Prasanna Das, Yu-Wen Lin, Utkarsha Agwan, Lucas Spangher, Alex Devonport, Yu Yang, Ján Drgona, Adrian Chong, Stefano Schiavon, Costas J. Spanos
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`	Proceedings of AAAI 2022 Fall Symposium: The Role of AI in Responding to Climate Challenges. CoRR Feras A. Batarseh, Priya L. Donti, Ján Drgona, Kristen Fletcher, Pierre-Adrien Hanania, Melissa Hatton, Srinivasan Keshav, Bran Knowles, Raphaela Kotsch, Sean McGinnis, Peetak Mitra, Alex Philp, Jim Spohrer, Frank Stein, Meghna Tare, Svitlana Volkov, Gege Wen
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`	Constructing Neural Network-Based Models for Simulating Dynamical Systems. CoRR Christian Møldrup Legaard, Thomas Schranz, Gerald Schweiger, Ján Drgona, Basak Falay, Cláudio Gomes, Alexandros Iosifidis, Mahdi Abkar, Peter Gorm Larsen
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	A*	`conf`	On the Stochastic Stability of Deep Markov Models. NeurIPS Ján Drgona, Sayak Mukherjee, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar
2021	J	`jnl`	On the Stochastic Stability of Deep Markov Models. CoRR Ján Drgona, Sayak Mukherjee, Jiaxin Zhang, Frank Liu, Mahantesh Halappanavar
2021	—	`conf`	The CityLearn Challenge 2022: Overview, Results, and Lessons Learned. NeurIPS (Competition and Demos) Kingsley Nweye, Zoltán Nagy, Sharada P. Mohanty, Dipam Chakraborty, Siva Sankaranarayanan, Tianzhen Hong, Sourav Dey, Gregor Henze, Ján Drgona, Fangquan Lin, Wei Jiang, Hanwei Zhang, Zhongkai Yi, Jihai Zhang, Cheng Yang, Matthew Motoki, Sorapong Khongnawang, Michael Ibrahim, Abilmansur Zhumabekov, Daniel May, Zhihu Yang, Xiaozhuang Song, Han Zhang, Xiaoning Dong, Shun Zheng, Jiang Bian
2021	—	`conf`	The second ACM SIGEnergy workshop on reinforcement learning for energy management in buildings & cities (RLEM). BuildSys Zoltán Nagy, June Young Park, Ján Drgona, Matias Quintana
2020	J	`jnl`	All you need to know about model predictive control for buildings. Annu. Rev. Control. Ján Drgona, Javier Arroyo, Iago Cupeiro Figueroa, David H. Blum, Krzysztof Arendt, Donghun Kim, Enric Perarnau Ollé, Juraj Oravec, Michael Wetter, Draguna L. Vrabie, Lieve Helsen
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`	Physics-Informed Neural State Space Models via Learning and Evolution. CoRR Elliott Skomski, Ján Drgona, Aaron Tuor
2020	J	`jnl`	Physics-constrained Deep Learning of Multi-zone Building Thermal Dynamics. CoRR Ján Drgona, Aaron Randall Tuor, Vikas Chandan, Draguna L. Vrabie
2020	J	`jnl`	Spectral Analysis and Stability of Deep Neural Dynamics. CoRR Ján Drgona, Elliott Skomski, Soumya Vasisht, Aaron Tuor, Draguna L. Vrabie
2018	J	`jnl`	MPC-based reference governor control of a continuous stirred-tank reactor. Comput. Chem. Eng. Juraj Holaza, Martin Klauco, Ján Drgona, Juraj Oravec, Michal Kvasnica, Miroslav Fikar
2017	J	`jnl`	Optimal control of a laboratory binary distillation column via regionless explicit MPC. Comput. Chem. Eng. Ján Drgona, Martin Klauco, Filip Janecek, Michal Kvasnica
2016	—	`conf`	Regionless explicit MPC of a distillation column. ECC Ján Drgona, Filip Janecek, Martin Klauco, Michal Kvasnica
2015	—	`conf`	MPC-based reference governors for thermostatically controlled residential buildings. CDC Ján Drgona, Martin Klauco, Michal Kvasnica
2013	—	`conf`	Explicit MPC of LPV systems in the controllable canonical form. ECC Michal Kvasnica, Alexander Szucs, Miroslav Fikar, Ján Drgona
2013	—	`conf`	Explicit stochastic MPC approach to building temperature control. CDC Ján Drgona, Michal Kvasnica, Martin Klauco, Miroslav Fikar