Maximum Likelihood Estimation of Regularization Parameters in High-Dimensional Inverse Problems: An Empirical Bayesian Approach Part I: Methodology and Experiments (2020)
Attributed to:
Bayesian model selection & calibration for computational imaging
funded by
EPSRC
Abstract
No abstract provided
Bibliographic Information
Digital Object Identifier: http://dx.doi.org/10.1137/20m1339829
Publication URI: http://dx.doi.org/10.1137/20m1339829
Type: Journal Article/Review
Parent Publication: SIAM Journal on Imaging Sciences
Issue: 4