AGE
AGE copied to clipboard
thunlp
Source code and dataset for KDD 2020 paper "Adaptive Graph Encoder for Attributed Graph Embedding"
AGE
Source code and datasets for KDD 2020 paper "Adaptive Graph Encoder for Attributed Graph Embedding"
Requirements
Please make sure your environment includes:
python (tested on 3.7.4)
pytorch (tested on 1.2.1)
Then, run the command:
pip install -r requirements.txt
Run
Run AGE on Cora dataset:
python train.py --dataset cora --gnnlayers 8 --upth_st 0.011 --lowth_st 0.1 --upth_ed 0.001 --lowth_ed 0.5
To reproduce the node clustering experiment results, please follow our hyper-parameter settings:
| Dataset | gnnlayers | upth_st | upth_ed | lowth_st | lowth_ed |
|---|---|---|---|---|---|
| Cora | 8 | 0.0110 | 0.0010 | 0.1 | 0.5 |
| Citeseer | 3 | 0.0015 | 0.0010 | 0.1 | 0.5 |
| Wiki | 1 | 0.0011 | 0.0010 | 0.1 | 0.5 |
| Pubmed | 35 | 0.0013 | 0.0010 | 0.7 | 0.8 |
For link prediction, please run link_pred.py. We did not tune hyper-parameters for link prediction, so you can tune all kinds of hyper-parameters to get better performance.
Cite
If you use the code, please cite our paper:
@inproceedings{cui2020adaptive,
title={Adaptive Graph Encoder for Attributed Graph Embedding},
author={Cui, Ganqu and Zhou, Jie and Yang, Cheng and Liu, Zhiyuan},
booktitle={Proceedings of SIGKDD 2020},
year={2020}
}
thunlp