A finite-element variational inference method delivers full-covariance Bayesian field reconstruction at dimensions exceeding 400,000 for 3D porous media flow using sparse precision parameterization from SPDE priors.
Solution of physics-based Bayesian inverse problems with deep generative priors
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Scalable High-Dimensional Bayesian Field Reconstruction with Finite Elements: Application to 3D Porous Media Flow
A finite-element variational inference method delivers full-covariance Bayesian field reconstruction at dimensions exceeding 400,000 for 3D porous media flow using sparse precision parameterization from SPDE priors.