This repo is for source code of NeurIPS 2022 paper "Revisiting Graph Contrastive Learning from the Perspective of Graph Spectrum".
Paper Link: https://arxiv.org/abs/2210.02330

Environment Settings

python==3.8.5
dgl==0.9.1
dgl_cu111==0.7.2
networkx==2.5
numpy==1.19.2
PyYAML==6.0
scikit_learn==1.1.2
scipy==1.6.2
torch==1.9.0
torch_geometric==1.7.2

GPU: GeForce RTX 3090
CPU: Intel(R) Xeon(R) Silver 4210 CPU @ 2.20GHz

Usage

First, go into the target folder. Then, run the following commands:

# DGI+SpCo
python execute.py cora --gpu=0

# GRACE+SpCo
python train.py cora --gpu_id=0

# CCA+SpCo
python main.py cora --gpu 0

where "cora" can be replaced by {citeseer, blog, flickr, pubmed}.
For each target model, we just add our SpCo on original code with some adaption. Therefore, you can refer to original code for better understanding about our code.

Cite

@inproceedings{spco,
  author       = {Nian Liu and
                  Xiao Wang and
                  Deyu Bo and
                  Chuan Shi and
                  Jian Pei},
  title        = {Revisiting Graph Contrastive Learning from the Perspective of Graph
                  Spectrum},
  booktitle    = {NeurIPS},
  year         = {2022}
}

Contact

If you have any questions, please feel free to contact me with {nianliu@bupt.edu.cn}