Hyperpriors for Matérn fields with applications in Bayesian inversion

From MaRDI portal
Publication:667766

DOI10.3934/ipi.2019001zbMath1454.60068arXiv1612.02989OpenAlexW2964007675MaRDI QIDQ667766

Markku Markkanen, Lassi Roininen, Sari Lasanen, Mark A. Girolami

Publication date: 1 March 2019

Published in: Inverse Problems and Imaging (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1612.02989




Related Items (19)

Cauchy Markov random field priors for Bayesian inversionComparing two populations using Bayesian Fourier series density estimationBayesian inversion techniques for stochastic partial differential equationsSparsity promoting reconstructions via hierarchical prior models in diffuse optical tomographyPosterior inference for sparse hierarchical non-stationary modelsHybrid iterative ensemble smoother for history matching of hierarchical modelsCauchy difference priors for edge-preserving Bayesian inversionOptimization-Based Markov Chain Monte Carlo Methods for Nonlinear Hierarchical Statistical Inverse ProblemsNon-stationary multi-layered Gaussian priors for Bayesian inversionStochastic modeling of geometrical uncertainties on complex domains, with application to additive manufacturing and brain interface geometriesFast sampling of parameterised Gaussian random fieldsBayesian inference of random fields represented with the Karhunen-Loève expansionStochastic modeling and identification of material parameters on structures produced by additive manufacturingPractical Heteroscedastic Gaussian Process Modeling for Large Simulation ExperimentsDiagnostics-Driven Nonstationary Emulators Using Kernel MixturesDeep state-space Gaussian processesSemivariogram methods for modeling Whittle–Matérn priors in Bayesian inverse problemsThe SPDE approach to Matérn fields: graph representationsGraph-based prior and forward models for inverse problems on manifolds with boundaries


Uses Software


Cites Work


This page was built for publication: Hyperpriors for Matérn fields with applications in Bayesian inversion