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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 111–120 of 192 papers

TitleStatusHype
Safe Physics-Informed Machine Learning for Dynamics and Control—0
Scalable algorithms for physics-informed neural and graph networks—0
Scientific machine learning in Hydrology: a unified perspective—0
Self-tuning moving horizon estimation of nonlinear systems via physics-informed machine learning Koopman modeling—0
Separable DeepONet: Breaking the Curse of Dimensionality in Physics-Informed Machine Learning—0
Slow Invariant Manifolds of Singularly Perturbed Systems via Physics-Informed Machine Learning—0
Solving engineering eigenvalue problems with neural networks using the Rayleigh quotient—0
Spectrally Informed Learning of Fluid Flows—0
Structural Constraints for Physics-augmented Learning—0
Tensor Basis Gaussian Process Models of Hyperelastic Materials—0
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