Jochen Stiasny

19 papers Journal 16Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Residual Power Flow for Neural Solvers. CoRR Jochen Stiasny, Jochen L. Cremer
2025	J	`jnl`	Data driven approach towards more efficient Newton-Raphson power flow calculation for distribution grids. CoRR Shengyuan Yan, Farzad Vazinram, Zeynab Kaseb, Lindsay Spoor, Jochen Stiasny, Betul Mamudi, Amirhossein Heydarian Ardakani, Ugochukwu Orji, Pedro P. Vergara, Yu Xiang, Jerry Guo
2025	J	`jnl`	PriceFM: Foundation Model for Probabilistic Electricity Price Forecasting. CoRR Runyao Yu, Chenhui Gu, Jochen Stiasny, Qingsong Wen, Wasim Sarwar Dilov, Lianlian Qi, Jochen L. Cremer
2024	J	`jnl`	Correctness Verification of Neural Networks Approximating Differential Equations. CoRR Petros Ellinas, Rahul Nellikkath, Ignasi Ventura, Jochen Stiasny, Spyros Chatzivasileiadis
2024	J	`jnl`	Error estimation for physics-informed neural networks with implicit Runge-Kutta methods. CoRR Jochen Stiasny, Spyros Chatzivasileiadis
2024	J	`jnl`	Integrating Physics-Informed Neural Networks into Power System Dynamic Simulations. CoRR Ignasi Ventura Nadal, Jochen Stiasny, Spyros Chatzivasileiadis
2023	J	`jnl`	Physics-Informed Neural Networks for Time-Domain Simulations: Accuracy, Computational Cost, and Flexibility. CoRR Jochen Stiasny, Spyros Chatzivasileiadis
2023	J	`jnl`	Solving Differential-Algebraic Equations in Power Systems Dynamics with Neural Networks and Spatial Decomposition. CoRR Jochen Stiasny, Spyros Chatzivasileiadis, Baosen Zhang
2022	—	`conf`	Accelerating Dynamical System Simulations with Contracting and Physics-Projected Neural-Newton Solvers. L4DC Samuel Chevalier, Jochen Stiasny, Spyros Chatzivasileiadis
2022	J	`jnl`	Bayesian Physics-Informed Neural Networks for Robust System Identification of Power Systems. CoRR Simon Stock, Jochen Stiasny, Davood Babazadeh, Christian Becker, Spyros Chatzivasileiadis
2022	J	`jnl`	Closing the Loop: A Framework for Trustworthy Machine Learning in Power Systems. CoRR Jochen Stiasny, Samuel Chevalier, Rahul Nellikkath, Brynjar Sævarsson, Spyros Chatzivasileiadis
2022	J	`jnl`	Interpretable Machine Learning for Power Systems: Establishing Confidence in SHapley Additive exPlanations. CoRR Robert I. Hamilton, Jochen Stiasny, Tabia Ahmad, Samuel Chevalier, Rahul Nellikkath, Ilgiz Murzakhanov, Spyros Chatzivasileiadis, Panagiotis N. Papadopoulos
2021	—	`conf`	Capturing Power System Dynamics by Physics-Informed Neural Networks and Optimization. CDC Georgios S. Misyris, Jochen Stiasny, Spyros Chatzivasileiadis
2021	J	`jnl`	Capturing Power System Dynamics by Physics-Informed Neural Networks and Optimization. CoRR Georgios S. Misyris, Jochen Stiasny, Spyros Chatzivasileiadis
2021	J	`jnl`	Contracting Neural-Newton Solver. CoRR Samuel Chevalier, Jochen Stiasny, Spyros Chatzivasileiadis
2021	—	`conf`	Learning without Data: Physics-Informed Neural Networks for Fast Time-Domain Simulation. SmartGridComm Jochen Stiasny, Samuel Chevalier, Spyros Chatzivasileiadis
2021	J	`jnl`	Learning without Data: Physics-Informed Neural Networks for Fast Time-Domain Simulation. CoRR Jochen Stiasny, Samuel Chevalier, Spyros Chatzivasileiadis
2021	J	`jnl`	Transient Stability Analysis with Physics-Informed Neural Networks. CoRR Jochen Stiasny, Georgios S. Misyris, Spyros Chatzivasileiadis
2020	J	`jnl`	Physics-Informed Neural Networks for Non-linear System Identification applied to Power System Dynamics. CoRR Jochen Stiasny, George S. Misyris, Spyros Chatzivasileiadis