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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 141–150 of 192 papers

TitleStatusHype
Valuation of Public Bus Electrification with Open Data—0
Physics-Informed Machine Learning of Dynamical Systems for Efficient Bayesian InferenceCode1
How important are activation functions in regression and classification? A survey, performance comparison, and future directions—0
STDEN: Towards Physics-Guided Neural Networks for Traffic Flow PredictionCode1
Physics-informed Machine Learning of Parameterized Fundamental Diagrams—0
Neural modal ordinary differential equations: Integrating physics-based modeling with neural ordinary differential equations for modeling high-dimensional monitored structuresCode0
Physics-informed machine learning for Structural Health Monitoring—0
Noise-aware Physics-informed Machine Learning for Robust PDE DiscoveryCode0
Physics-informed machine learning with differentiable programming for heterogeneous underground reservoir pressure managementCode1
Residual-based physics-informed transfer learning: A hybrid method for accelerating long-term CFD simulations via deep learning—0
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