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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 126–150 of 192 papers

TitleStatusHype
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning—0
Neural-Integrated Meshfree (NIM) Method: A differentiable programming-based hybrid solver for computational mechanics—0
Physical Data Embedding for Memory Efficient AI—0
Numerical Approximation in CFD Problems Using Physics Informed Machine Learning—0
Numerical Gaussian process Kalman filtering for spatiotemporal systems—0
Optimal Power Flow in Highly Renewable Power System Based on Attention Neural Networks—0
Overview of Physics-Informed Machine Learning Inversion of Geophysical Data—0
Grid-SiPhyR: An end-to-end learning to optimize framework for combinatorial problems in power systems—0
Physics-Informed Computer Vision: A Review and Perspectives—0
Physics-informed ConvNet: Learning Physical Field from a Shallow Neural Network—0
Physics-Informed Deep B-Spline Networks for Dynamical Systems—0
Physics-informed Gaussian process model for Euler-Bernoulli beam elements—0
Physics-Informed Induction Machine Modelling—0
Physics-informed machine learning for Structural Health Monitoring—0
Physics Informed Machine Learning for Chemistry Tabulation—0
Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems—0
Physics-informed Machine Learning for Calibrating Macroscopic Traffic Flow Models—0
Physics-Informed Machine Learning for Microscale Drying of Plant-Based Foods: A Systematic Review of Computational Models and Experimental Insights—0
Physics-Informed Machine Learning for Efficient Reconfigurable Intelligent Surface Design—0
Physics-informed machine learning for building performance simulation-A review of a nascent field—0
Physics-informed Machine Learning for Battery Pack Thermal Management—0
Physics-Informed Machine Learning for Data Anomaly Detection, Classification, Localization, and Mitigation: A Review, Challenges, and Path Forward—0
Physics-Informed Machine Learning for Grade Prediction in Froth Flotation—0
Physics-informed machine learning for moving load problems—0
Physics-Informed Machine Learning for Seismic Response Prediction OF Nonlinear Steel Moment Resisting Frame Structures—0
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