/examples/mxnet/rgcn

Relational-GCN

• Paper: https://arxiv.org/abs/1703.06103
• Author's code for entity classification: https://github.com/tkipf/relational-gcn
• Author's code for link prediction: https://github.com/MichSchli/RelationPrediction

Dependencies

Two extra python packages are needed for this example:

• MXNet nightly build
• requests
• rdflib
• pandas

pip install mxnet --pre
pip install requests rdflib pandas

Example code was tested with rdflib 4.2.2 and pandas 0.23.4

Entity Classification

AIFB: accuracy 97.22% (DGL), 95.83% (paper)

DGLBACKEND=mxnet python3 entity_classify.py -d aifb --testing --gpu 0

MUTAG: accuracy 73.53% (DGL), 73.23% (paper)

DGLBACKEND=mxnet python3 entity_classify.py -d mutag --l2norm 5e-4 --n-bases 40 --testing --gpu 0

BGS: accuracy 75.86% (DGL, n-basese=20, OOM when >20), 83.10% (paper)

DGLBACKEND=mxnet python3 entity_classify.py -d bgs --l2norm 5e-4 --n-bases 20 --testing --gpu 0 --relabel