Bayesian sparsity and class sparsity priors for dictionary learning and coding

A Bocchinfuso, D Calvetti, E Somersalo - arXiv preprint arXiv:2309.00999, 2023 - arxiv.org
Dictionary learning methods continue to gain popularity for the solution of challenging
inverse problems. In the dictionary learning approach, the computational forward model is …

[HTML][HTML] Bayesian sparsity and class sparsity priors for dictionary learning and coding

A Bocchinfuso, D Calvetti, E Somersalo - Journal of Computational …, 2024 - Elsevier
Dictionary learning methods continue to gain popularity for the solution of challenging
inverse problems. In the dictionary learning approach, the computational forward model is …

Hierarchical Bayesian Inverse Problems: A High-Dimensional Statistics Viewpoint

D Sanz-Alonso, N Waniorek - arXiv preprint arXiv:2401.03074, 2024 - arxiv.org
This paper analyzes hierarchical Bayesian inverse problems using techniques from high-
dimensional statistics. Our analysis leverages a property of hierarchical Bayesian …

Mathematical Modeling of Gas Transport Across Cell Membrane: Forward and Inverse Problems

A Bocchinfuso - 2023 - search.proquest.com
Two of the many functions supporting life, pH regulations and gas exchange, appear to be
related and many studies have been conducted on the gas exchange across cell …

[PDF][PDF] Group sparsity promotion via Bayesian hierarchical models in dictionary learning/coding

D Calvetti - sites.uci.edu
Group sparsity promotion via Bayesian hierarchical models in dictionary learning/coding Page
1 0. Group sparsity promotion via Bayesian hierarchical models in dictionary learning/coding …

Hierarchical Bayesian models for EEG, MEG and beyond

E Somersaloa - PROCEEDINGS OF SIMAI 2023 - unibas.it
Erkki Somersaloa a Department of Mathematics, Applied Mathematics and Statistics, Case
Western Reserve University (USA) ejs49@ case. edu In this talk, a review of hierarchical …