Hands-on Tutorial on Graph Deep Learning

Material for the hands-on tutorial on Graph Deep Learning within the Machine Learning and Dynamical Systems Seminar, hosted by the Alan Turing Institute.

Recordings available here.

Full schedule available here

• Part I: November 2, Presenter: Gabriele Santin
  • Goals: Motivations, Intro of basic concepts, definition of GNNs.
  • Material: Slides Video.
• Part II: November 9, Presenter: Antonio Longa
  • Goals: Implementation of GNNs: How to implement a full GNN pipeline in PyTorch Geometric.
  • Material: Slides, Code, Video.
• Part III: November 16, Presenter: Steve Azzolin
  • Goals: Explainability of GNNs: How to inspect a model understanding the learned decision pattern.
  • Material: Slides, Code, Video
• Part IV: November 23, Presenter: Francesco Ferrini
  • Goals: Heterogeneity in GNNs: How can GNNs effectively model and incorporate a diversity of nodes and edges with different types.
  • Material: Coming soon.