An intro to Graph Neural Networks 🕸️🧠

Graph Neural Networks have seen a rise in popularity. This is no surprise since various forms of information can be understood in the context of graphs from social networks to molecules. This notebook intends to illuminate the inner workings of Graph Convolutional Networks and give an intuition into some other types of Networks which extend this idea.

Environment and Kernel Setup

If you work on the clara/paula cluster load python:

ml Python/3.9.5-GCCcore-10.3.0

or Anaconda

ml Anaconda3/2021.11

and then create the environment with the respective dependencies:

conda env create n "PyG" -f environment.yml

Activate the environment

conda activate PyG

Now create a kernel to use in the Jupyter Notebook

ipython kernel install --user --name "PyG" --display-name "PyG"

Now you can go to the JupyterLab, select the kernel PyG and run the notebook.