Self-supervised Graph-level Representation Learning with Local and Global Structure
GraphLoG
This project is an implementation of ‘Self-supervised Graph-level Representation Learning with Local and Global Structure’ in PyTorch, which is accepted as Short Talk by ICML 2021. We provide the pre-training and fine-tuning codes and also the pre-trained model on chemistry domain in this repository, and a more complete code version including the biology domain will be announced on the TorchDrug platform developed by MilaGraph group. Also, we would like to appreciate the excellent work of Pretrain-GNNs which lays a solid foundation for our work.
More details of this work can be found in our paper: [Paper (arXiv)].
Prerequisites
We develop this project with Python3.6 and following Python packages:
Pytorch 1.1.0
torch-cluster 1.4.5
torch-geometric 1.0.3
torch-scatter 1.4.0
torch-sparse 0.4.4
torch-spline-conv 1.0.6
rdkit 2019.03.1