Title and abstract of the planned talk
Gitta Kutyniok is a German applied mathematician known for her research in harmonic analysis, compressed sensing, and image processing.
She held positions of Einstein Professor of Mathematics and a professor of computer science and electrical engineering at the Technical University of Berlin.
She is the first AI professor at LMU Munich, starting her new position from 01.10.2020.
The title and abstract of the planned talk are on the right side.
Title: “Deep Learning and Modeling: Taking the Best out of Both Worlds”
Abstract: Pure model-based approaches are today often insufficient for solving complex inverse problems in imaging. At the same time, we witness the tremendous success of data-based methodologies, in particular, deep neural networks for such problems. However, pure deep learning approaches often neglect known and valuable information from the modeling world.
In this talk, we will provide an introduction to this problem complex and then discuss a general conceptual approach to inverse problems in imaging, which combines data-based and model-based methods. This hybrid approach is based on shearlet-based sparse regularization and deep learning, and is guided by a microlocal analysis viewpoint to pay particular attention to the singularity structures of the data. Finally, we will present several applications such as tomographic reconstruction and show that our approach outperforms previous methodologies, including methods entirely based on deep learning.