Second-Order Pooling for Graph Neural Networks

This is the code for our paper "Second-Order Pooling for Graph Neural Networks". It is based on the code from GIN. Many thanks!

Created by Zhengyang Wang and Shuiwang Ji at Texas A&M University.

Download & Citation

The paper is now available at IEEE Xplore. If you use our code or results, please kindly cite our paper.

@article{wang2020second,
  author={Wang, Zhengyang and Ji, Shuiwang},
  title={Second-Order Pooling for Graph Neural Networks},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, 
  year={2020},
  publisher={IEEE}
}

System requirement

Programming language

Python 3.6

Python Packages

PyTorch > 1.0.0, tqdm, networkx, numpy

Setup

If you want to try our proposed second-order pooling methods, copy the graphcnn.py file into the models folder from either the sopool_bilinear folder (bilinear second-order pooling) or the sopool_attn folder (attentional second-order pooling).

Run the code

We provide scripts to run the experiments. For bioinformatics datasets and the REDDIT datasets, run

chmod +x run_bio.sh
./run_bio.sh [DATASET] [GPU_ID] [BATCH_SIZE] [HIDDEN_DIM]

For the social network datasets, run

chmod +x run_social.sh
./run_social.sh [DATASET] [GPU_ID] [BATCH_SIZE] [HIDDEN_DIM]