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Found 3 papers, 2 papers with code
$Φ$-DVAE: Physics-Informed Dynamical Variational Autoencoders for Unstructured Data Assimilation
To address these shortcomings, in this paper we develop a physics-informed dynamical variational autoencoder ($\Phi$-DVAE) to embed diverse data streams into time-evolving physical systems described by differential equations.
Statistical Finite Elements via Langevin Dynamics
Through embedding uncertainty inside of the governing equations, finite element solutions are updated to give a posterior distribution which quantifies all sources of uncertainty associated with the model.
Low-rank statistical finite elements for scalable model-data synthesis
Statistical learning additions to physically derived mathematical models are gaining traction in the literature.
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