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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 91–100 of 192 papers

TitleStatusHype
Physics-informed machine learning of redox flow battery based on a two-dimensional unit cell model—0
Physics-informed machine learning of the correlation functions in bulk fluids—0
Physics-Informed Machine Learning On Polar Ice: A Survey—0
Physics Informed Machine Learning (PIML) methods for estimating the remaining useful lifetime (RUL) of aircraft engines—0
Physics-Informed Machine Learning Regulated by Finite Element Analysis for Simulation Acceleration of Laser Powder Bed Fusion—0
Physics-Informed Machine Learning Towards A Real-Time Spacecraft Thermal Simulator—0
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
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