Code for AAAI 2024 paper "ReGCL: Rethinking Message Passing in Graph Contrastive Learning".
- Python 3.8
- PyTorch 1.13.1+ cu117
- torch-geometric 2.3.0
- torch-scatter 2.1.0
- torch-sparse 0.6.15
- torch-spline-conv 1.2.1
- pyyaml 6.0.1
- scikit-learn 1.3.0
- numpy 1.21.6
Citation Networks: 'Cora', 'Citeseer' and 'Pubmed'.
Co-occurence Networks: 'Amazon-Photo', 'Coauthor-CS'
| Dataset | # Nodes | # Edges | # Classes | # Features |
|---|---|---|---|---|
| Cora | 2,708 | 10,556 | 7 | 1,433 |
| Citeseer | 3,327 | 9,228 | 6 | 3,703 |
| Pubmed | 19,717 | 88,651 | 3 | 500 |
| Amazon-Photo | 7,650 | 287,326 | 8 | 745 |
| Coauthor-CS | 18,333 | 327,576 | 15 | 6,805 |
To run the codes, use the following commands:
#test:
python train.py --dataset Cora --test
#train:
python train.py --dataset Cora --lr 5e-4 --tau 0.2 --dfr1 0.4 --dfr2 0.4 --der1 0.0 --der2 0.4