Can Virtual Nodes Improve Node Classification on Heterophilic Graphs?

This repository contains the code for the untitled research project on virtual nodes in GNNs, by Sepand Dyanatkar and Jamie Weigold.

Setup and usage

git clone git@github.com:DSep/virtual-nodes.git
cd virtual-nodes
git submodule update --init --recursive
pip install -r requirements.txt
pip install -e Heterophily_and_oversmoothing
pip install -e understanding_oversquashing
pip install -e .

To avoid dependency conflicts, it is highly recommended that our code is run in a fresh conda/miniconda environment which can be easily configured (if running mac OSX) by executing the following in a terminal:

conda create -n virtual_nodes python=3.9
conda activate virtual_nodes
conda install pytorch torchvision -c pytorch
conda install pyg -c pyg
conda install -c dglteam dgl

Running experiments

Start in the root directory of the repository

sh virtual_nodes/experiments/method1.sh

Or on the server:

nohup bash virtual_nodes/experiments/method1.sh > TIME_DAY_03_2023_method1.log 2> nohup.err < /dev/null &

TODOS:

• Add setup.py files for top level and submodules to make easy referencing from anywhere (aka Heterophily and curvature folders)
• Setup proper testing in home directory and move tests to this folder