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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 151–160 of 192 papers

TitleStatusHype
A Physics-Informed Machine Learning Framework for Safe and Optimal Control of Autonomous Systems—0
A Physics-Informed Machine Learning Model for Porosity Analysis in Laser Powder Bed Fusion Additive Manufacturing—0
A physics-informed machine learning model for reconstruction of dynamic loads—0
A Physics-informed machine learning model for time-dependent wave runup prediction—0
Applying physics-based loss functions to neural networks for improved generalizability in mechanics problems—0
A Review of Physics-Informed Machine Learning Methods with Applications to Condition Monitoring and Anomaly Detection—0
Beyond Accuracy: EcoL2 Metric for Sustainable Neural PDE Solvers—0
Breaking the Diffraction Barrier for Passive Sources: Parameter-Decoupled Superresolution Assisted by Physics-Informed Machine Learning—0
BridgeNet: A Hybrid, Physics-Informed Machine Learning Framework for Solving High-Dimensional Fokker-Planck Equations—0
Calibrating constitutive models with full-field data via physics informed neural networks—0
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