## 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