Sparse exit wave reconstruction via deep unfolding (A08)

• Subject Area: Mathematics
• Term: since 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 442047500

The aim of this project is to introduce hybrid models for exit wave reconstruction, a problem from electron microscopy and a variant of phase retrieval, using deep unfolding and to understand the behavior of the resulting neural networks, e.g., their generalization properties. We systematically explore which network parameters are most beneficial for learning, considering different variants of data term and regularizer, focussing on sparsity inducing regularizers like the 1-norm. These are combined with a sparsity basis that is introduced as network parameter shared among the layers.

• DFG Programme: Collaborative Research Centres
• Subproject of: SFB 1481: Sparsity and Singular Structures
• Applicant Institution: Rheinisch-Westfälische Technische Hochschule Aachen
• Project Head: Professor Dr. Benjamin Berkels