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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 31–40 of 192 papers

TitleStatusHype
A Physics-Informed Machine Learning Framework for Safe and Optimal Control of Autonomous Systems—0
A Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study—0
AI Foundation Models for Weather and Climate: Applications, Design, and Implementation—0
A Physics-informed Machine Learning-based Control Method for Nonlinear Dynamic Systems with Highly Noisy Measurements—0
A Physics-Informed Machine Learning Approach for Solving Distributed Order Fractional Differential Equations—0
Advancing Hybrid Quantum Neural Network for Alternative Current Optimal Power Flow—0
A comprehensive and FAIR comparison between MLP and KAN representations for differential equations and operator networks—0
Discovering nonlinear resonances through physics-informed machine learning—0
A Physics-Informed Machine Learning Approach for Solving Heat Transfer Equation in Advanced Manufacturing and Engineering Applications—0
Physics-informed machine learning for composition-process-property alloy design: shape memory alloy demonstration—0
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