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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 131–140 of 192 papers

TitleStatusHype
Physics-Informed Machine Learning for Efficient Reconfigurable Intelligent Surface Design—0
Potential failures of physics-informed machine learning in traffic flow modeling: theoretical and experimental analysis—0
TS-PIELM: Time-Stepping Physics-Informed Extreme Learning Machine Facilitates Soil Consolidation Analyses—0
AutoMat: Accelerated Computational Electrochemical systems Discovery—0
A Comparative Evaluation of Additive Separability Tests for Physics-Informed Machine Learning—0
A comprehensive and FAIR comparison between MLP and KAN representations for differential equations and operator networks—0
A Critical Review of Physics-Informed Machine Learning Applications in Subsurface Energy Systems—0
A Data-driven Crowd Simulation Framework Integrating Physics-informed Machine Learning with Navigation Potential Fields—0
AdjointNet: Constraining machine learning models with physics-based codes—0
Advancing Hybrid Quantum Neural Network for Alternative Current Optimal Power Flow—0
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