Ján Drgona

Orcid: 0000-0003-1223-208X

Affiliations:
  • Pacific Northwest National Laboratory (PNNL), Richland, WA, USA
  • KU Leuven, Belgium
  • Slovak University of Technology, Bratislava, Slovakia (PhD)


According to our database1, Ján Drgona authored at least 38 papers between 2013 and 2024.

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Bibliography

2024
Semi-supervised Learning of Dynamical Systems with Neural Ordinary Differential Equations: A Teacher-Student Model Approach.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Constructing Neural Network Based Models for Simulating Dynamical Systems.
ACM Comput. Surv., November, 2023

Robust Differentiable Predictive Control with Safety Guarantees: A Predictive Safety Filter Approach.
CoRR, 2023

Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory.
CoRR, 2023

Power Grid Behavioral Patterns and Risks of Generalization in Applied Machine Learning.
Proceedings of the Companion Proceedings of the 14th ACM International Conference on Future Energy Systems, 2023

Data-Driven Control: Theory and Applications.
Proceedings of the American Control Conference, 2023

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems.
Proceedings of the American Control Conference, 2023

AutoNF: Automated Architecture Optimization of Normalizing Flows with Unconstrained Continuous Relaxation Admitting Optimal Discrete Solution.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Proceedings of AAAI 2022 Fall Symposium: The Role of AI in Responding to Climate Challenges.
CoRR, 2022

Machine Learning for Smart and Energy-Efficient Buildings.
CoRR, 2022

Domain-aware Control-oriented Neural Models for Autonomous Underwater Vehicles.
CoRR, 2022

Structural Inference of Networked Dynamical Systems with Universal Differential Equations.
CoRR, 2022

Neuro-physical dynamic load modeling using differentiable parametric optimization.
CoRR, 2022

Learning Stochastic Parametric Differentiable Predictive Control Policies.
CoRR, 2022

Data-driven Stabilization of Discrete-time Control-affine Nonlinear Systems: A Koopman Operator Approach.
Proceedings of the European Control Conference, 2022

Differentiable Predictive Control with Safety Guarantees: A Control Barrier Function Approach.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Neural Lyapunov Differentiable Predictive Control.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

Neural Ordinary Differential Equations for Nonlinear System Identification.
Proceedings of the American Control Conference, 2022

Koopman-based Differentiable Predictive Control for the Dynamics-Aware Economic Dispatch Problem.
Proceedings of the American Control Conference, 2022

2021
Deep Learning Explicit Differentiable Predictive Control Laws for Buildings.
CoRR, 2021

The second ACM SIGEnergy workshop on reinforcement learning for energy management in buildings & cities (RLEM).
Proceedings of the BuildSys '21: The 8th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, Coimbra, Portugal, November 17, 2021


On the Stochastic Stability of Deep Markov Models.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Automating Discovery of Physics-Informed Neural State Space Models via Learning and Evolution.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Constrained Block Nonlinear Neural Dynamical Models.
Proceedings of the 2021 American Control Conference, 2021

2020
Physics-Informed Neural State Space Models via Learning and Evolution.
CoRR, 2020

Spectral Analysis and Stability of Deep Neural Dynamics.
CoRR, 2020

Physics-constrained Deep Learning of Multi-zone Building Thermal Dynamics.
CoRR, 2020

Differentiable Predictive Control: An MPC Alternative for Unknown Nonlinear Systems using Constrained Deep Learning.
CoRR, 2020

Constrained Physics-Informed Deep Learning for Stable System Identification and Control of Unknown Linear Systems.
CoRR, 2020

Constrained Neural Ordinary Differential Equations with Stability Guarantees.
CoRR, 2020

All you need to know about model predictive control for buildings.
Annu. Rev. Control., 2020

2018
MPC-based reference governor control of a continuous stirred-tank reactor.
Comput. Chem. Eng., 2018

2017
Optimal control of a laboratory binary distillation column via regionless explicit MPC.
Comput. Chem. Eng., 2017

2016
Regionless explicit MPC of a distillation column.
Proceedings of the 15th European Control Conference, 2016

2015
MPC-based reference governors for thermostatically controlled residential buildings.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

2013
Explicit MPC of LPV systems in the controllable canonical form.
Proceedings of the 12th European Control Conference, 2013

Explicit stochastic MPC approach to building temperature control.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013


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