Graph Neural Networks: A gentle introduction

Resources that was very useful for me when learning about GNNs that you can check out for more information and from which I've used in the slides:

Cs224w: https://youtube.com/playlist?l....ist=PLoROMvodv4rPLKx
https://distill.pub/2021/gnn-intro/
https://distill.pub/2021/understanding-gnns/
https://www.youtube.com/playli....st?list=PLV8yxwGOxvv
https://youtu.be/8owQBFAHw7E
https://youtu.be/uF53xsT7mjc
https://youtu.be/w6Pw4MOzMuo

0:00 Introduction
1:24 Why graphs
4:13 What is a graph
7:06 Common graph tasks
11:08 Representation of a graph
12:46 - How does a GNN work?
14:35 - Understanding information propagation
17:24 - Key property: Permutation Invariance
19:33 - Key property: Permutation Equivariance
22:22 - Message passing computation
23:53 - GNN Variant: Convolution
26:37 - GNN Variant: Attention
28:39 - Ending