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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 11–20 of 192 papers

TitleStatusHype
Physics-constrained deep learning postprocessing of temperature and humidityCode1
Fleet Prognosis with Physics-informed Recurrent Neural NetworksCode1
Physics informed machine learning with Smoothed Particle Hydrodynamics: Hierarchy of reduced Lagrangian models of turbulenceCode1
Physics-Informed Machine Learning Simulator for Wildfire PropagationCode1
Analyzing Koopman approaches to physics-informed machine learning for long-term sea-surface temperature forecastingCode1
A physics-informed neural network for wind turbine main bearing fatigueCode1
Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaicsCode1
Finite Operator Learning: Bridging Neural Operators and Numerical Methods for Efficient Parametric Solution and Optimization of PDEsCode1
Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systemsCode1
Physics-informed neural networks for corrosion-fatigue prognosisCode1
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