Scaling Up Bayesian Uncertainty Quantification for Inverse Problems Using Deep Neural Networks

DOI10.1137/21m1439456zbMath1514.62009arXiv2101.03906MaRDI QIDQ6109143

Shuyi Li, Babak Shahbaba, Shiwei Lan

Publication date: 30 June 2023

Published in: SIAM/ASA Journal on Uncertainty Quantification (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2101.03906

zbMATH Keywords

autoencoderdimension reductionemulationBayesian inverse problemsconvolutional neural networkensemble Kalman methods

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Artificial neural networks and deep learning (68T07) Probabilistic methods, particle methods, etc. for initial value and initial-boundary value problems involving PDEs (65M75)

Related Items (2)

Component-wise iterative ensemble Kalman inversion for static Bayesian models with unknown measurement error covariance ⋮ Bayesian spatiotemporal modeling for inverse problems

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