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SCINet should be included in PyPOTS, and could start from the imputation task.
@inproceedings{liu2022scinet,
author = {LIU, Minhao and Zeng, Ailing and Chen, Muxi and Xu, Zhijian and LAI, Qiuxia and Ma, Lingna and Xu, Qiang},
booktitle = {Advances in Neural Information Processing Systems},
editor = {S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh},
pages = {5816--5828},
publisher = {Curran Associates, Inc.},
title = {SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction},
url = {https://proceedings.neurips.cc/paper_files/paper/2022/file/266983d0949aed78a16fa4782237dea7-Paper-Conference.pdf},
volume = {35},
year = {2022}
}
2. Check open-source status
The model implementation is publicly available
3. Provide useful information for the implementation
1. Model description
SCINet 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/cure-lab/SCINet
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