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Graph Convolutional Networks (GCN)

Dependencies

  • Tensorflow 2.1+
  • requests

bash pip install tensorflow requests export DGLBACKEND=tensorflow

Codes

The folder contains three implementations of GCN:

  • gcn.py uses DGL's predefined graph convolution module.
  • gcn_mp.py uses user-defined message and reduce functions.
  • gcn_builtin.py improves from gcn_mp.py by using DGL's builtin functions so SPMV optimization could be applied.

Results

Run with following (available dataset: "cora", "citeseer", "pubmed")

python3 train.py --dataset cora --gpu 0 --self-loop
  • cora: ~0.810 (0.79-0.83) (paper: 0.815)
  • citeseer: 0.707 (paper: 0.703)
  • pubmed: 0.792 (paper: 0.790)