STGNN

The pytorch implementation of Traffic Flow Prediction via Spatial Temporal Graph Neural Network

Further Reading

1. When Spatio-Temporal Meet Wavelets: Disentangled Traffic Forecasting via Efficient Spectral Graph Attention Networks, in ICDE 2023. [GitHub Repo]

Authors: Yuchen Fang, Yanjun Qin, Haiyong Luo, Fang Zhao, Bingbing Xu, Liang Zeng, Chenxing Wang.

@inproceedings{fang2023spatio,
  title={When spatio-temporal meet wavelets: Disentangled traffic forecasting via efficient spectral graph attention networks},
  author={Fang, Yuchen and Qin, Yanjun and Luo, Haiyong and Zhao, Fang and Xu, Bingbing and Zeng, Liang and Wang, Chenxing},
  booktitle={2023 IEEE 39th International Conference on Data Engineering (ICDE)},
  pages={517--529},
  year={2023}
}

2. Efficient Large-Scale Traffic Forecasting with Transformers: A Spatial Data Management Perspective, in SIGKDD 2025. [GitHub Repo]

Authors: Yuchen Fang, Yuxuan Liang, Bo Hui, Zezhi Shao, Liwei Deng, Xu Liu, Xinke Jiang, Kai Zheng.

@article{fang2024efficient,
  title={Efficient Large-Scale Traffic Forecasting with Transformers: A Spatial Data Management Perspective},
  author={Fang, Yuchen and Liang, Yuxuan and Hui, Bo and Shao, Zezhi and Deng, Liwei and Liu, Xu and Jiang, Xinke and Zheng, Kai},
  journal={arXiv preprint arXiv:2412.09972},
  year={2024}
}