Graph Transformer Networks
This repository is the implementation of Graph Transformer Networks(GTN).
Seongjun Yun, Minbyul Jeong, Raehyun Kim, Jaewoo Kang, Hyunwoo J. Kim, Graph Transformer Networks, In Advances in Neural Information Processing Systems (NeurIPS 2019).
Dependencies
Running the code
$ mkdir data
$ cd data
Download datasets (DBLP, ACM, IMDB) from this link and extract data.zip into data folder.
$ cd ..
- DBLP
$ python main.py --dataset DBLP --num_layers 3
- ACM
$ python main.py --dataset ACM --num_layers 2 --adaptive_lr true
- IMDB
$ python main_sparse.py --dataset IMDB --num_layers 3 --adaptive_lr true
Citation
If this work is useful for your research, please cite our paper:
@inproceedings{yun2019graph,
title={Graph Transformer Networks},
author={Yun, Seongjun and Jeong, Minbyul and Kim, Raehyun and Kang, Jaewoo and Kim, Hyunwoo J},
booktitle={Advances in Neural Information Processing Systems},
pages={11960--11970},
year={2019}
}