Bayesian estimation of Karhunen-Loève expansions; a random subspace approach

DOI10.1016/j.jcp.2016.02.056zbMath1349.65008OpenAlexW2338231641MaRDI QIDQ726884

Kenny Chowdhary, Habib N. Najm

Publication date: 5 December 2016

Published in: Journal of Computational Physics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jcp.2016.02.056

zbMATH Keywords

principal component analysisMarkov chain Monte CarloBayesian inferenceGibbs samplinguncertainty quantificationKarhunen-Loève expansionmatrix Bingham density

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Bayesian inference (62F15) General second-order stochastic processes (60G12) Monte Carlo methods (65C05)

Related Items (4)

A stabilized POD model for turbulent flows over a range of Reynolds numbers: optimal parameter sampling and constrained projection ⋮ Compressive sensing adaptation for polynomial chaos expansions ⋮ Bayesian adaptation of chaos representations using variational inference and sampling on geodesics ⋮ Karhunen–Loeve expansion for the additive two-sided Brownian motion

Uses Software

• rstiefel

Cites Work

• Unnamed Item
• A tutorial on approximate Bayesian computation
• Principal component analysis.
• Statistics on special manifolds
• Estimation of covariance matrices based on hierarchical inverse-Wishart priors
• Spectral Representation and Reduced Order Modeling of the Dynamics of Stochastic Reaction Networks via Adaptive Data Partitioning
• On the Karhunen-Loeve expansion for transformed processes
• Spectral Methods for Uncertainty Quantification
• Probabilistic Principal Component Analysis
• A Visual Explanation of Jensen's Inequality
• On the numerical expansion of a second order stochastic process

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