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

This example does not contain the implementation of PPNP.

Dataset Statics

Dataset # Nodes # Edges # Classes
Cora 2,708 10,556 7
Citeseer 3,327 9,228 6
Pubmed 19,717 88,651 3
cora-ml 2810 7981 7

Results

TL_BACKEND="paddle" python appnp_trainer.py --dataset cora --lr 0.15 --n_epoch 200 --hidden_dim 64 --drop_rate 0.4 --l2_coef 0.02 --iter_K 6 --self_loops 0
TL_BACKEND="paddle" python appnp_trainer.py --dataset pubmed --lr 0.2 --n_epoch 250 --hidden_dim 64 --drop_rate 0.6 --l2_coef 0.001 --iter_K 10 --self_loops 2
TL_BACKEND="paddle" python appnp_trainer.py --dataset citeseer --lr 0.03 --n_epoch 500 --hidden_dim 32 --alpha 0.1 --drop_rate 0.4 --l2_coef 2e-3 --iter_K 10 --self_loops 1
dataset paper our(pd) our(tf)
cora 82.9(±0.56) 76.3(±0.45)
citeseer 75.83(±0.27) 70.8(±0.00) 65.7(±0.15)
pubmed 79.73(±0.31) 79.8(±0.67) 75.5(±0)
cora-ml 85.29(±0.25)