Project Details
Projekt
Signal processing on graphs and complexes (A07)
Subject Area
Mathematics
Term
since 2022
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 442047500
The goal of this project is to advance our understanding of graph neural networks and related signal processing methods for data defined on non-Euclidean domains. We will explore two selected facets within this broad area: a) how the structure of the domain on which theneural network is defined constrains its expressibility, and b) how the structure of the neural network influences its training via gradient descent and related algorithms. In both cases we concentrate on the roles of symmetries and (approximate) low rank structures within those networks, i.e., low-dimensional (sparse) substructures within these networks.
DFG Programme
Collaborative Research Centres
Subproject of
SFB 1481:
Sparsity and Singular Structures
Applicant Institution
Rheinisch-Westfälische Technische Hochschule Aachen
Project Head
Professor Michael Schaub, Ph.D.
