readme.md

AM-GCN: Adaptive Multi-channel Graph Convolutional Networks (AM-GCN)

• Paper link: https://dl.acm.org/doi/10.1145/3394486.3403177
• Author's code repo: https://github.com/BUPT-GAMMA/AM-GCN. Note that the original code is implemented with PyTorch 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=torch python amgcn_trainer.py --dataset cora --lr 0.0005 --k 6 --hidden1 512 --hidden2 32 --drop_rate 0.5 --beta 1e-10 --theta 0.0001
TL_BACKEND=torch python amgcn_trainer.py --dataset citeseer --lr 0.0005 --k 7 --hidden1 768 --hidden2 256 --drop_rate 0.5 --beta 5e-10 --theta 0.001
TL_BACKEND=torch python amgcn_trainer.py --dataset pubmed --lr 0.0005 --k 6 --hidden1 512 --hidden2 128 --drop_rate 0.5 --beta 5e-10 --theta 0.001

Dataset	Paper	Our(th)
cora		79.5(±0.3)
citeseer	73.1	71.7(±1.2)
pubmed		64.4(±0.8)