SOTAVerified

Physics-informed machine learning

Machine learning used to represent physics-based and/or engineering models

Papers

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Showing 71–80 of 192 papers

TitleStatusHype
Machine Learning with Physics Knowledge for Prediction: A Survey—0
Towards Model Reduction for Power System Transients with Physics-Informed PDE—0
KKANs: Kurkova-Kolmogorov-Arnold Networks and Their Learning Dynamics—0
BridgeNet: A Hybrid, Physics-Informed Machine Learning Framework for Solving High-Dimensional Fokker-Planck Equations—0
Label Propagation Training Schemes for Physics-Informed Neural Networks and Gaussian Processes—0
Calibrating constitutive models with full-field data via physics informed neural networks—0
(Un)supervised Learning of Maximal Lyapunov Functions—0
Learning ergodic averages in chaotic systems—0
Data-driven AC Optimal Power Flow with Physics-informed Learning and Calibrations—0
Identifying Ordinary Differential Equations for Data-efficient Model-based Reinforcement Learning—0
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