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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 101–110 of 192 papers

TitleStatusHype
Physics-informed Modularized Neural Network for Advanced Building Control by Deep Reinforcement Learning—0
Physics-informed neural networks for pathloss prediction—0
A Metalearning Approach for Physics-Informed Neural Networks (PINNs): Application to Parameterized PDEs—0
Residual-based physics-informed transfer learning: A hybrid method for accelerating long-term CFD simulations via deep learning—0
Scalable Neural Dynamic Equivalence for Power Systems—0
Predicting 3D Rigid Body Dynamics with Deep Residual Network—0
Prediction of Reynolds Stresses in High-Mach-Number Turbulent Boundary Layers using Physics-Informed Machine Learning—0
QRnet: optimal regulator design with LQR-augmented neural networks—0
Randomized Physics-Informed Machine Learning for Uncertainty Quantification in High-Dimensional Inverse Problems—0
Replication Study: Enhancing Hydrological Modeling with Physics-Guided Machine Learning—0
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