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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 111–120 of 192 papers

TitleStatusHype
Optimal Power Flow in Highly Renewable Power System Based on Attention Neural Networks—0
Neural-Integrated Meshfree (NIM) Method: A differentiable programming-based hybrid solver for computational mechanics—0
A Physics-informed Machine Learning-based Control Method for Nonlinear Dynamic Systems with Highly Noisy Measurements—0
Filtered Partial Differential Equations: a robust surrogate constraint in physics-informed deep learning framework—0
Zero Coordinate Shift: Whetted Automatic Differentiation for Physics-informed Operator LearningCode0
Overview of Physics-Informed Machine Learning Inversion of Geophysical Data—0
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
AI Foundation Models for Weather and Climate: Applications, Design, and Implementation—0
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