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Physics-informed machine learning

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

Papers

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Showing 101–110 of 192 papers

TitleStatusHype
Scalable Neural Dynamic Equivalence for Power Systems—0
Predicting 3D Rigid Body Dynamics with Deep Residual Network—0
Prediction of Reynolds Stresses in High-Mach-Number Turbulent Boundary Layers using Physics-Informed Machine Learning—0
QRnet: optimal regulator design with LQR-augmented neural networks—0
Randomized Physics-Informed Machine Learning for Uncertainty Quantification in High-Dimensional Inverse Problems—0
Replication Study: Enhancing Hydrological Modeling with Physics-Guided Machine Learning—0
Safe Physics-Informed Machine Learning for Dynamics and Control—0
Scalable algorithms for physics-informed neural and graph networks—0
Scientific machine learning in Hydrology: a unified perspective—0
Self-tuning moving horizon estimation of nonlinear systems via physics-informed machine learning Koopman modeling—0
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