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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 81–90 of 192 papers

TitleStatusHype
Discrete-Time Nonlinear Feedback Linearization via Physics-Informed Machine Learning—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
TS-PIELM: Time-Stepping Physics-Informed Extreme Learning Machine Facilitates Soil Consolidation Analyses—0
Discovering nonlinear resonances through physics-informed machine learning—0
Discovering Artificial Viscosity Models for Discontinuous Galerkin Approximation of Conservation Laws using Physics-Informed Machine Learning—0
A Physics-Informed Machine Learning Approach for Solving Heat Transfer Equation in Advanced Manufacturing and Engineering Applications—0
Neural-Integrated Meshfree (NIM) Method: A differentiable programming-based hybrid solver for computational mechanics—0
Differentiable Predictive Control for Large-Scale Urban Road Networks—0
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