Bayesian Computations for Large-scale (Nonlinear) Inverse Problems in Imaging

During research stays with the collaborating group at Caltech, we aim to investigate various aspects of statistical inverse problems. This includes inquiries into particle- and PDE-based sampling methods, as well as robust regularization using neural networks.

Project partners

Prof. Franca Hoffmann, California Institute of Technology, USA

Involved Helmholtz Imaging Units

Research Unit DESY

Primary Contact

Lorenz Kuger

lorenz.kuger@desy.de

Prof. Dr. Martin Burger

martin.burger@desy.de

Other projects

QGRIS: Quantitative Gamma-Ray Imaging System

Compton cameras are used for the radiological characterization of nuclear power plants. In this project, a suitable camera system is designed, and the associated algorithms for image reconstruction and nuclide characterization are implemented as user software.

SFB Transregio 154 – C06: Transport metrics for analysis and optimization of network problems

SFB TRR 154 is a project of the German Research Foundation (DFG) and combines integer-continuous methods, model adaptation, and numerical simulation, to analyze and optimize gas markets, infrastructure, and control of networks. The third funding period specifically focuses on the transition from natural gas to hydrogen.