Graphlevel-SSL

Overview

Apply Graph Self-Supervised Learning methods to graph-level task(TUDataset, MolculeNet Dataset).
It is unified framework to compare state-of-the art graph-level self-supervised learning method with two well-known dataset(TUDataset, MoleculeNet Dataset).

I only focused on linear protocol which is two step method

1. pretrain with self-supervied method
2. freeze encoder and only train classifier

Reference

I adopt various official codes to unify below methods. I expect that it can ensure very fair comparision.

• InfoGraph : https://github.com/fanyun-sun/InfoGraph
• GraphCL : https://github.com/Shen-Lab/GraphCL
• MVGRL : https://github.com/kavehhassani/mvgrl
• GCA : https://github.com/CRIPAC-DIG/GCA
• BGRL(not official code) : https://github.com/Namkyeong/BGRL_Pytorch

How to Run

TUDataset

git clone https://github.com/LJS-Student/Graphlevel-SSL.git
cd Unsup_TU
mkdir results
sh example.sh

MoleculeNet Dataset

you can download MoleculeNet Dataset here

cd Unsup_Mol
mkdir results
sh example.sh

GitHub

GitHub - LJS-Student/Graphlevel-SSL: Apply Graph Self-Supervised Learning methods to graph-level task(TUDataset, MolculeNet Datset)

Apply Graph Self-Supervised Learning methods to graph-level task(TUDataset, MolculeNet Datset) - GitHub - LJS-Student/Graphlevel-SSL: Apply Graph Self-Supervised Learning methods to graph-level tas...

GitHubLJS-Student