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