Graph Convolutional Networks (GCN) Paper link: https://arxiv.org/abs/1609.02907 Author's code repo: https://github.com/tkipf/gcn. Note that the original code is implemented with Tensorflow for the paper. Dataset Statics Dataset # Nodes # Edges # Classes Cora 2,708 10,556 7 Citeseer 3,327 9,228 6 Pubmed 19,717 88,651 3 Refer to Planetoid. Results # available dataset: "cora", "citeseer", "pubmed" TL_BACKEND="paddle" python gcn_trainer.py --dataset cora --lr 0.01 --l2_coef 0.005 --drop_rate 0.9 TL_BACKEND="paddle" python gcn_trainer.py --dataset citeseer --lr 0.01 --l2_coef 0.01 --drop_rate 0.7 TL_BACKEND="paddle" python gcn_trainer.py --dataset pubmed --lr 0.01 --l2_coef 0.005 --drop_rate 0.6 Dataset Paper Our(pd) Our(tf) cora 81.5 81.83±0.22 80.54±1.12 citeseer 70.3 70.38±0.78 68.34±0.68 pubmed 79.0 78.62±0.30 78.28±1.08