2017 - Inverse Problems and Imaging
This summer school considered the analytical and numerical treatment of inverse problems in the context of multi-modal and hybrid schemes as well as in imaging. A particular focus was set on adapted sparsity regularization and suitable numerical algorithms.
The school was particularly interesting for advanced Master students, PhD students and PostDocs working on inverse problems, on imaging, or on related subjects.
|Prof. Dr. Simon Arridge||University College, United Kingdom|
|Prof. Dr. Guillaume Bal||University of Chicago, United States|
|Prof. Dr. Antonin Chambolle||CNRS/Ecole Polytechnique, France|
|Prof. Dr. Dirk Lorenz||Universität Braunschweig, Germany|
Lectures covered the following topics in the general framework of inverse problems and imaging.
- Multi-modal inverse problems
- Hybrid methods for inverse problems
- Sparsity regularization
- Algorithms for sparsity regularization
For more infornation visit the Oficial Website.