## Kinetic Methods for Inverse Problems

Photo-acoustic tomography (PAT) exploits an interaction between electromagnetic and acoustic phenomena. Accordingly, a standard forward model underlying PAT involves an elliptic PDE with internal data coupled with a hyperbolic initial-boundary problem. For both component problems one can formulate a forward operator that maps a feature of the sampl...

In this thesis we introduce a framework for parallel MCMC methods which we call parallel adaptive importance sampling (PAIS). At each iteration we have an ensemble of particles, from which PAIS builds a kernel density estimate (KDE). We propose a new ensemble, using this KDE, that is weighted according to standard importance sampling rules. A state...

Trinity College, University of Cambridge

Trinity College, University of Cambridge

Trinity College, University of Cambridge

Trinity College, University of Cambridge

This paper deals with microwave tomography for brain stroke imaging using state-of-the-art numerical modeling and massively parallel computing. Iterative microwave tomographic imaging requires the solution of an inverse problem based on a minimization algorithm (e.g. gradient or Newton-like methods) with successive solutions of a direct problem. Th...

This paper deals with microwave tomography for brain stroke imaging using state-of-the-art numerical modeling and massively parallel computing. Iterative microwave tomographic imaging requires the solution of an inverse problem based on a minimization algorithm (e.g. gradient or Newton-like methods) with successive solutions of a direct problem. Th...

This paper deals with microwave tomography for brain stroke imaging using state-of-the-art numerical modeling and massively parallel computing. Iterative microwave tomographic imaging requires the solution of an inverse problem based on a minimization algorithm (e.g. gradient or Newton-like methods) with successive solutions of a direct problem. Th...