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
FITS should be included in PyPOTS, and could start from the imputation task.
@inproceedings{xu2024fits,
title={{FITS}: Modeling Time Series with \$10k\$ Parameters},
author={Zhijian Xu and Ailing Zeng and Qiang Xu},
booktitle={The Twelfth International Conference on Learning Representations},
year={2024},
url={https://openreview.net/forum?id=bWcnvZ3qMb}
}
2. Check open-source status
[X] The model implementation is publicly available
3. Provide useful information for the implementation
1. Model description
FITS 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/VEWOXIC/FITS