- Paper link: Predict then Propagate: Graph Neural Networks meet Personalized PageRank
- Author's code repo: https://github.com/klicperajo/ppnp.
- MXNET 1.5+
- requests
bash pip install torch requests
The folder contains an implementation of APPNP (appnp.py
).
Run with following (available dataset: "cora", "citeseer", "pubmed")
DGLBACKEND=mxnet python3 appnp.py --dataset cora --gpu 0
- cora: 0.8370 (paper: 0.850)
- citeseer: 0.713 (paper: 0.757)
- pubmed: 0.798 (paper: 0.797)
Experiments were done on dgl datasets (GCN settings) which are different from those used in the original implementation. (discrepancies are detailed in experimental section of the original paper)