7 papers
Spotlight, priorsketching and Bayesian approximation error paradigms
Daniela Calvetti, Erkki Somersalo
A way to lower computational cost in large scale inverse problems and problems depending on poorly known model parameters is to replace the detailed model by an approximate one. In…
Sparse Dictionary-Based Solution of Dynamic Inverse Problems
Aidan Mason-Mackay, Daniela Calvetti, Erkki Somersalo +4
In ill-posed dynamic inverse problems expected spatial features and temporal correlation between frames can be leveraged to improve the quality of the computed solution, in particu…
Discretization-free Bayesian inverse problems in distribution spaces
Daniela Calvetti, Erkki Somersalo
The Bayesian approach to inverse problems provides a practical way to solve ill-posed problems by augmenting the observation model with prior information. Due to its measure-theore…
Bayesian dictionary learning estimation of cell membrane permeability from surface pH data
Alberto Bocchinfuso, Daniela Calvetti, Erkki Somersalo
Gas transport across cell membrane is a very important process in biochemistry which is essential for many crucial tasks, including cell respiration pH regulation in the cell. In t…
Spotlight inversion by orthogonal projections
Daniela Calvetti, Nuutti Hyvönen, Ville Kolehmainen +1
Many computational problems involve solving a linear system of equations, although only a subset of the entries of the solution are needed. In inverse problems, where the goal is t…
Dictionary learning methods for brain activity mapping with MEG data
Daniela Calvetti, Erkki Somersalo
A central goal in many brain studies is the identification of those brain regions that are activated during an observation window that may correspond to a motor task, a stimulus, o…