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GMAN: A Graph Multi-Attention Network for Traffic Prediction (AAAI-2020)
<p align="center"> <img width="600" height="450" src=./figure/GMAN.png> </p>This is the implementation of Graph Multi-Attention Network in the following paper:
Chuanpan Zheng, Xiaoliang Fan*, Cheng Wang, and Jianzhong Qi. "GMAN: A Graph Multi-Attention Network for Traffic Prediction", Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), 2020, 34(01): 1234-1241.
Data
The datasets are available at Google Drive or Baidu Yun, provided by DCRNN, and should be put into the corresponding data/ folder.
Requirements
Python 3.7.10, tensorflow 1.14.0, numpy 1.16.4, pandas 0.24.2
Results
<p align="center"> <img width="900" height="400" src=./figure/results.png> </p>Third-party re-implementations
A Pytorch implementaion by VincLee8188 is available at GMAN-Pytorch.
Citation
If you find this repository useful in your research, please cite the following paper:
@inproceedings{ GMAN-AAAI2020,
author = "Chuanpan Zheng and Xiaoliang Fan and Cheng Wang and Jianzhong Qi"
title = "GMAN: A Graph Multi-Attention Network for Traffic Prediction",
booktitle = "AAAI",
pages = "1234--1241",
year = "2020"
}