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Jochen Stiasny
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2020 – today
- 2024
- [i13]Jochen Stiasny, Spyros Chatzivasileiadis:
Error estimation for physics-informed neural networks with implicit Runge-Kutta methods. CoRR abs/2401.05211 (2024) - [i12]Petros Ellinas, Rahul Nellikkath, Ignasi Ventura, Jochen Stiasny, Spyros Chatzivasileiadis:
Correctness Verification of Neural Networks Approximating Differential Equations. CoRR abs/2402.07621 (2024) - [i11]Ignasi Ventura Nadal, Jochen Stiasny, Spyros Chatzivasileiadis:
Integrating Physics-Informed Neural Networks into Power System Dynamic Simulations. CoRR abs/2404.13325 (2024) - 2023
- [i10]Jochen Stiasny, Spyros Chatzivasileiadis:
Physics-Informed Neural Networks for Time-Domain Simulations: Accuracy, Computational Cost, and Flexibility. CoRR abs/2303.08994 (2023) - [i9]Jochen Stiasny, Spyros Chatzivasileiadis, Baosen Zhang:
Solving Differential-Algebraic Equations in Power Systems Dynamics with Neural Networks and Spatial Decomposition. CoRR abs/2303.10256 (2023) - 2022
- [c3]Samuel Chevalier, Jochen Stiasny, Spyros Chatzivasileiadis:
Accelerating Dynamical System Simulations with Contracting and Physics-Projected Neural-Newton Solvers. L4DC 2022: 803-816 - [i8]Jochen Stiasny
, Samuel Chevalier
Closing the Loop: A Framework for Trustworthy Machine Learning in Power Systems. CoRR abs/2203.07505 (2022) - [i7]Robert I. Hamilton
Interpretable Machine Learning for Power Systems: Establishing Confidence in SHapley Additive exPlanations. CoRR abs/2209.05793 (2022) - [i6]Simon Stock, Jochen Stiasny, Davood Babazadeh, Christian Becker, Spyros Chatzivasileiadis:
Bayesian Physics-Informed Neural Networks for Robust System Identification of Power Systems. CoRR abs/2212.11911 (2022) - 2021
- [c2]Georgios S. Misyris, Jochen Stiasny, Spyros Chatzivasileiadis:
Capturing Power System Dynamics by Physics-Informed Neural Networks and Optimization. CDC 2021: 4418-4423 - [c1]Jochen Stiasny
Learning without Data: Physics-Informed Neural Networks for Fast Time-Domain Simulation. SmartGridComm 2021: 438-443 - [i5]Georgios S. Misyris, Jochen Stiasny, Spyros Chatzivasileiadis:
Capturing Power System Dynamics by Physics-Informed Neural Networks and Optimization. CoRR abs/2103.17004 (2021) - [i4]Samuel Chevalier, Jochen Stiasny, Spyros Chatzivasileiadis:
Contracting Neural-Newton Solver. CoRR abs/2106.02543 (2021) - [i3]Jochen Stiasny, Georgios S. Misyris, Spyros Chatzivasileiadis:
Transient Stability Analysis with Physics-Informed Neural Networks. CoRR abs/2106.13638 (2021) - [i2]Jochen Stiasny, Samuel Chevalier, Spyros Chatzivasileiadis:
Learning without Data: Physics-Informed Neural Networks for Fast Time-Domain Simulation. CoRR abs/2106.15987 (2021) - 2020
- [i1]Jochen Stiasny, George S. Misyris, Spyros Chatzivasileiadis:
Physics-Informed Neural Networks for Non-linear System Identification applied to Power System Dynamics. CoRR abs/2004.04026 (2020)
Coauthor Index
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