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