Block Modeling-Guided Graph Convolutional Neural Networks

This repository contains the demo code of the paper:

Block Modeling-Guided Graph Convolutional Neural Networks

which has been accepted by AAAI2022.

Dependencies

• Python3.7
• NumPy
• SciPy
• PyTorch
• TensorFlow.keras

Example Usages

Before running the code， please unzip the data_geom.zip and make a directory named checkpoint.

• python main.py --dataset cora --enhance 3.0 --self_loop 1.5
• python main.py --dataset citeseer --enhance 4.0 --self_loop 2.0
• python main.py --dataset pubmed --enhance 2.0 --self_loop 3.0
• python main.py --dataset squirrel --enhance 2.0 --self_loop 0.0
• python main.py --dataset chameleon --enhance 0.8 --self_loop 0.0
• python main.py --dataset texas --num_gcn_layers 2 --enhance 1.0 --self_loop 0.0

Please refer to the args.py for more parameters.

Reference

If you make advantage of BM-GCN in your research, please cite the following in your manuscript:

Dongxiao He, et al. "Block Modeling-Guided Graph Convolutional Neural Networks." In AAAI. 2022.

License

Tianjin University