Low-Rank Eigenvector Compression of Posterior Covariance Matrices for Linear Gaussian Inverse Problems.
Peter BennerYue QiuMartin StollPublished in: SIAM/ASA J. Uncertain. Quantification (2018)
Keyphrases
- low rank
- covariance matrix
- convex optimization
- linear combination
- singular value decomposition
- principal component analysis
- missing data
- sample size
- probability distribution
- semi supervised
- high dimensional data
- high order
- bayesian framework
- gaussian process
- image reconstruction
- least squares
- partial differential equations
- maximum likelihood
- probabilistic model
- bayesian networks