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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
An operator preconditioning perspective on training in physics-informed machine learning—0
Physics-Informed Induction Machine Modelling—0
Scalable Neural Dynamic Equivalence for Power Systems—0
Physics-Informed Machine Learning for Data Anomaly Detection, Classification, Localization, and Mitigation: A Review, Challenges, and Path Forward—0
AI Foundation Models for Weather and Climate: Applications, Design, and Implementation—0
Physics-informed neural networks for highly compressible flowsCode1
Slow Invariant Manifolds of Singularly Perturbed Systems via Physics-Informed Machine Learning—0
Estimating irregular water demands with physics-informed machine learning to inform leakage detectionCode0
Separable Hamiltonian Neural NetworksCode0
Physics-informed machine learning of the correlation functions in bulk fluids—0
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