A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputation/classification/clustering/forecasting/anomaly detection/cleaning on incomplete industrial (irregularly-sampled) multivariate TS with NaN missing values
SegRNN should be included in PyPOTS, and could start from the imputation task.
@article{lin2023segrnn,
title={SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting},
author={Shengsheng Lin and Weiwei Lin and Wentai Wu and Feiyu Zhao and Ruichao Mo and Haotong Zhang},
year={2023},
eprint={2308.11200},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
2. Check open-source status
[x] The model implementation is publicly available
3. Provide useful information for the implementation
1. Model description
SegRNN 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/lss-1138/SegRNN