This is an implementation of Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting
python run_stode.py
- python 3.7
- torch 1.7.0+cu101
- torchdiffeq 0.2.2
- fastdtw 0.3.4
The datasets used in our paper are collected by the Caltrans Performance Measurement System(PeMS). Please refer to STSGCN (AAAI2020) for the download url.
Please cite our paper if you use the model in your own work:
@inproceedings{fang2021spatial,
title={Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting},
author={Fang, Zheng and Long, Qingqing and Song, Guojie and Xie, Kunqing},
booktitle={Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery \& Data Mining},
pages={364--373},
year={2021}
}