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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 71–80 of 192 papers

TitleStatusHype
Physics-informed kernel learningCode0
Non-overlapping, Schwarz-type Domain Decomposition Method for Physics and Equality Constrained Artificial Neural NetworksCode0
A Physics-Informed Machine Learning Approach for Solving Distributed Order Fractional Differential Equations—0
State-space models are accurate and efficient neural operators for dynamical systemsCode0
(Un)supervised Learning of Maximal Lyapunov Functions—0
Spectrally Informed Learning of Fluid Flows—0
Machine Learning with Physics Knowledge for Prediction: A Survey—0
Enhanced BPINN Training Convergence in Solving General and Multi-scale Elliptic PDEs with Noise—0
Physics-Informed Machine Learning for Grade Prediction in Froth Flotation—0
Self-tuning moving horizon estimation of nonlinear systems via physics-informed machine learning Koopman modeling—0
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