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Physics-Informed Neural Networks for Time-Domain Simulations: Accuracy,
Computational Cost, and Flexibility

v1v2 (latest)

Physics-Informed Neural Networks for Time-Domain Simulations: Accuracy, Computational Cost, and Flexibility

Electric power systems research (EPSR), 2023

15 March 2023

Spyros Chatzivasileiadis

ArXiv (abs)PDF HTML

Papers citing "Physics-Informed Neural Networks for Time-Domain Simulations: Accuracy, Computational Cost, and Flexibility"

2 / 2 papers shown

Learning Discontinuous Galerkin Solutions to Elliptic Problems via Small Linear Convolutional Neural Networks

Learning Discontinuous Galerkin Solutions to Elliptic Problems via Small Linear Convolutional Neural Networks

David T. Fuentes

Beatrice Riviere

297

0

0

12 Feb 2025

Correctness Verification of Neural Networks Approximating Differential
Equations

Correctness Verification of Neural Networks Approximating Differential Equations

Rahul Nellikkath

Spyros Chatzivasileiadis

224

3

0

12 Feb 2024

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