DFDGCN
Dynamic frequency domain graph convolution for traffic prediction
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DFDGCN
Dynamic Frequency Domain Graph Convolutional Network for Traffic Forecasting
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
If you have questions please email liyujie23s@ict.ac.cn or liyujie231@mails.ucas.ac.cn
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