The Power of Graph Learning | Richard M. Karp Distinguished Lecture

Floris Geerts analyses the expressive power of graph-learning methods. Predictions on graph-structured data must respect isomorphism, motivating invariant operations such as neighbourhood aggregation. The lecture connects these compositional operations with database theory to explain what different graph-learning architectures can represent, with applications including molecules, social networks and recommendation systems.