Files
dgl/examples/pytorch/appnp
2023-08-03 13:49:34 +08:00
..
2022-09-26 21:46:32 +08:00
2019-05-23 10:38:05 +08:00
2023-08-03 13:49:34 +08:00

Predict then Propagate: Graph Neural Networks meet Personalized PageRank (APPNP)

Dependencies

  • PyTorch 0.4.1+
  • requests

bash pip install torch requests

Code

The folder contains an implementation of APPNP (appnp.py).

Results

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

python3 train.py --dataset cora --gpu 0
  • cora: 0.8370 (paper: 0.850)
  • citeseer: 0.715 (paper: 0.757)
  • pubmed: 0.793 (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)