Skip to content
No description, website, or topics provided.
Python
Branch: master
Clone or download
Latest commit 3c9ca30 May 17, 2019
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
src modified: train.py Apr 21, 2019
README.md Update README.md May 17, 2019

README.md

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.

You can’t perform that action at this time.