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
As an interesting work, TEFN should be included in PyPOTS, and could start from the imputation task. The author @ztxtech would like to make contributions to accomplish this and maintain the model in the future. Thanks to Tianxiang.
@article{zhan2024tefn,
title={Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting},
author={Zhan, Tianxiang and He, Yuanpeng and Li, Zhen and Deng, Yong},
journal={arXiv preprint arXiv:2405.06419},
year={2024}
}
2. Check open-source status
[X] The model implementation is publicly available
3. Provide useful information for the implementation
1. Model description
As an interesting work, TEFN should be included in PyPOTS, and could start from the imputation task. The author @ztxtech would like to make contributions to accomplish this and maintain the model in the future. Thanks to Tianxiang.
2. Check open-source status
3. Provide useful information for the implementation
https://github.com/ztxtech/Time-Evidence-Fusion-Network