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FreTS should be included in PyPOTS, and could start from the imputation task.
@inproceedings{yi2023frets,
author = {Yi, Kun and Zhang, Qi and Fan, Wei and Wang, Shoujin and Wang, Pengyang and He, Hui and An, Ning and Lian, Defu and Cao, Longbing and Niu, Zhendong},
booktitle = {Advances in Neural Information Processing Systems},
editor = {A. Oh and T. Neumann and A. Globerson and K. Saenko and M. Hardt and S. Levine},
pages = {76656--76679},
publisher = {Curran Associates, Inc.},
title = {Frequency-domain MLPs are More Effective Learners in Time Series Forecasting},
url = {https://proceedings.neurips.cc/paper_files/paper/2023/file/f1d16af76939f476b5f040fd1398c0a3-Paper-Conference.pdf},
volume = {36},
year = {2023}
}
2. Check open-source status
The model implementation is publicly available
3. Provide useful information for the implementation
1. Model description
FreTS should be included in PyPOTS, and could start from the imputation task.
2. Check open-source status
3. Provide useful information for the implementation
https://github.com/aikunyi/FreTS
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