Variable order smoothness priors for ill-posed inverse problems

DOI10.1090/S0025-5718-2014-02909-8zbMath1309.65045MaRDI QIDQ5246839

Erkki Somersalo, Daniela Calvetti, Ruben D. Spies

Publication date: 22 April 2015

Published in: Mathematics of Computation (Search for Journal in Brave)

Mathematics Subject Classification ID

Ill-posedness and regularization problems in numerical linear algebra (65F22) Probabilistic models, generic numerical methods in probability and statistics (65C20)

Related Items (1)

Sparsity-promoting and edge-preserving maximum a posteriori estimators in non-parametric Bayesian inverse problems

Uses Software

• Regularization tools
• UTV

Cites Work

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• Time series: theory and methods
• Statistical and computational inverse problems.
• Fitting autoregressive models for prediction
• Conditionally Gaussian Hypermodels for Cerebral Source Localization
• A Gaussian hypermodel to recover blocky objects
• Hypermodels in the Bayesian imaging framework
• Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter
• The Use of the L-Curve in the Regularization of Discrete Ill-Posed Problems
• Analysis of bounded variation penalty methods for ill-posed problems
• Rank-Deficient and Discrete Ill-Posed Problems
• Inverse Problem Theory and Methods for Model Parameter Estimation
• Iterative Methods for Total Variation Denoising
• Introduction to Bayesian Scientific Computing
• Non-negativity and iterative methods for ill-posed problems

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