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DFDGCN

Dynamic frequency domain graph convolution for traffic prediction

Install / Use

/learn @GestaltCogTeam/DFDGCN
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

DFDGCN

Dynamic Frequency Domain Graph Convolutional Network for Traffic Forecasting

preprint

This paper has been accepted by ICASSP2024.

We appreciate you reviewing our work and you can use it if you want to cite it:

@inproceedings{li2024dynamic,
  title={Dynamic Frequency Domain Graph Convolutional Network for Traffic Forecasting},  
  author={Li, Yujie and Shao, Zezhi and Xu, Yongjun and Qiu, Qiang and Cao, Zhaogang and Wang, Fei},
  booktitle={ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={5245--5249},
  year={2024},
  organization={IEEE}
}

Acknowledgement:

Our work is developed based on BasicTS, if you are interested in more work on time series forecasting, you can refer to this Standard and Fair Time Series Forecasting Benchmark and Toolkit: https://github.com/GestaltCogTeam/BasicTS

Github

If you have questions please email liyujie23s@ict.ac.cn or liyujie231@mails.ucas.ac.cn

Related Skills

View on GitHub
GitHub Stars70
CategoryDevelopment
Updated2mo ago
Forks3

Languages

Jupyter Notebook

Security Score

95/100

Audited on Jan 7, 2026

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