Seminar: Graph Learning (PhD course)

In this seminar, we cover different neural-network architectures for representing graphs. The participants read and present selected papers, which will be discussed during the meetings.

The following topics will be covered:

• Graph Convolutional Networks (GCN)
• Graph Neural Networks (GNN)
• Message-Passing Neural Networks (MPNN)
• Graph Transformer Architectures
• Expressive Power of different Architectures
• Applications in Symbolic Reasoning

Course Information

• Examiner: Daniel Gnad