Awesome
DAG-GNN
Code for DAG-GNN work
Getting Started
Prerequisites
Python 3.7
PyTorch >1.0
How to Run
Synthetic data experiments
Synthetic Experiments
CHOICE = linear, nonlinear_1, or nonlinear_2, corresponding to the experiments in the paper
python train.py --graph_linear_type=<CHOICE>
Cite
If you make use of this code in your own work, please cite our paper:
@inproceedings{yu2019dag,
title={DAG-GNN: DAG Structure Learning with Graph Neural Networks},
author={Yue Yu, Jie Chen, Tian Gao, and Mo Yu},
booktitle={Proceedings of the 36th International Conference on Machine Learning},
year={2019}
}
Acknowledgments
Our work and code benefit from two existing works, which we are very grateful.
- DAG NOTEAR https://github.com/xunzheng/notears
- Neural relational inference for interacting systems https://github.com/ethanfetaya/nri