- Paper link: https://arxiv.org/abs/1609.02907
- Author's code repo: https://github.com/tkipf/gcn. Note that the original code is implemented with Tensorflow for the paper.
The folder contains two implementations of GCN. gcn_batch.py uses user-defined
message and reduce functions. gcn_spmv.py uses DGL's builtin functions so
SPMV optimization could be applied.
Run with following (available dataset: "cora", "citeseer", "pubmed")
python gcn_spmv.py --dataset cora --gpu 0- cora: ~0.810 (0.79-0.83) (paper: 0.815)
- citeseer: 0.707 (paper: 0.703)
- pubmed: 0.792 (paper: 0.790)