What You Always Wanted to Know about Graph Embeddings (And Never Dared to Ask)

Speaker: Dr Ismail Ilkan Ceylan (University of Oxford)

Seminar Summary

This talk will present the core methodologies and techniques for deep learning with graph-structured data along with some recent advances and open problems. We will start by answering questions such as “why learning representations of graphs are useful?” firmly linking learned graph representations to various application domains — particularly applications in life sciences. We will then move on to the question of “what are the common principles behind existing (successful) graph learning architectures?” which will be answered staring from first principles. We will then discuss some existing challenges and how they are addressed in our recent works (and how they open more avenues for future work). This talk is tailored for a rather broad audience and no specific background will be assumed.

Registration will be open until 10 October.