2017 - Inverse Problems and Imaging
This summer school considers 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 is set on adapted sparsity regularization and suitable numerical algorithms.
The school is particularly interesting for advanced Master students, PhD students and PostDocs working on inverse problems, on imaging, or on related subjects.
- Simon Arridge (University College, London)
- Guillaume Bal (Columbia University, New York)
- Antonin Chambolle (CNRS/Ecole Polytechnique, Palaiseau)
- Dirk Lorenz (Universität Braunschweig)
Lectures will cover 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.