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Local Augmentation for Graph Neural Networks

This repository contains an implementation of "Local Augmentation for Graph Neural Networks".

Dependencies

  • CUDA 10.2.89
  • python 3.6.8
  • pytorch 1.9.0
  • pyg 2.0.3

Usage

  • For semi-supervised setting, run the following script
cd Citation
bash semi.sh
  • For full-supervised setting, run the following script
cd OGB
# If you want to pre-train the generative model, run the following command:
python cvae_generate_products.py --latent_size 10 --pretrain_lr 1e-5 --total_iterations 10000 --batch_size 8192
# Train downstream GNNs
bash full.sh

Citation

@inproceedings{liu2022local,
  title={Local augmentation for graph neural networks},
  author={Liu, Songtao and Ying, Rex and Dong, Hanze and Li, Lanqing and Xu, Tingyang and Rong, Yu and Zhao, Peilin and Huang, Junzhou and Wu, Dinghao},
  booktitle={International Conference on Machine Learning},
  year={2022}
}