5 papers
Sparsity-promoting hierarchical Bayesian model for EIT with a blocky target
Daniela Calvetti, Monica Pragliola, Erkki Somersalo
The electrical impedance tomography (EIT) problem of estimating the unknown conductivity distribution inside a domain from boundary current or voltage measurements requires the sol…
An efficient hierarchical Bayesian method for the Kuopio tomography challenge 2023
Monica Pragliola, Daniela Calvetti, Erkki Somersalo
The aim of Electrical Impedance Tomography (EIT) is to determine the electrical conductivity distribution inside a domain by applying currents and measuring voltages on its boundar…
Overcomplete representation in a hierarchical Bayesian framework
Monica Pragliola, Daniela Calvetti, Erkki Somersalo
A common task in inverse problems and imaging is finding a solution that is sparse, in the sense that most of its components vanish. In the framework of compressed sensing, general…
Sparsity promoting hybrid solvers for hierarchical Bayesian inverse problems
Daniela Calvetti, Monica Pragliola, Erkki Somersalo
The recovery of sparse generative models from few noisy measurements is an important and challenging problem. Many deterministic algorithms rely on some form of - m…
Computational issues and numerical experiments for Linear Multistep Method Particle Filtering
Daniela Calvetti, Salvatore Cuomo, Monica Pragliola +2
The Linear Multistep Method Particle Filter (LMM PF) is a method for predicting the evolution in time of a evolutionary system governed by a system of differential equations. If so…