Week 6

Author

Huanfa Chen

Published

March 25, 2026

Introduction

This week, we’ll explore how to generalise neural networks to graph-structured data and introduce the classic types of graph neural networks.

Learning Objectives

By the end of this week, you will be able to:

  1. Understand the design and training of graph neural networks.
  2. Understand the common types of graph neural networks.
  3. Can apply graph neural networks to real-world graph-structured data.

Lecture

To access the lecture notes: Lecture

Quiz

To access the quiz on Moodle, please check Moodle page.

Practical

Note

To save a copy of notebook to your own GitHub Repo: follow the GitHub link, click on Raw and then Save File As... to save it to your own computer. Make sure to change the extension from .ipynb.txt (which will probably be the default) to .ipynbbefore adding the file to your GitHub repository.

To access the practical:

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Further resources