SelfTask-GNN

A PyTorch implementation of "Self-supervised Learning on Graphs: Deep Insights and New Directions". [paper]

In this paper, we first deepen our understandings on when, why, and which strategies of SSL work with GNNs by empirically studying numerous basic SSL pretext tasks on graphs. Inspired by deep insights from the empirical studies, we propose a new direction SelfTask to build advanced pretext tasks that are able to achieve state-of-the-art performance on various real-world datasets.

Requirements

See that in https://github.com/ChandlerBang/SelfTask-GNN/blob/master/requirements.txt

Run our code

Clone the repository

git clone https://github.com/ChandlerBang/SelfTask-GNN.git
cd SelfTask-GNN
pip install -r requirements.txt

You need to further install ica package

pip uninstall ica # in case you have installed it before
git clone https://github.com/ChandlerBang/ica.git 
cd ica
python setup.py install

To reproduce the performance reported in the paper, you can run the bash files in folder scripts.

sh scripts/selftask/cora_CorrectedLabel_ICA.sh
sh scripts/selftask/cora_CorrectedLabel_LP.sh

Acknowledgement

This repository is modified from DropEdge (https://github.com/DropEdge/DropEdge). We sincerely thank them for their contributions.

Cite

For more information, you can take a look at the paper

If you find this repo to be useful, please cite our paper. Thank you.

@misc{jin2020selfsupervised,
    title={Self-supervised Learning on Graphs: Deep Insights and New Direction},
    author={Wei Jin and Tyler Derr and Haochen Liu and Yiqi Wang and Suhang Wang and Zitao Liu and Jiliang Tang},
    year={2020},
    eprint={2006.10141},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}