Citation and Milestones#

Citing PyPOTS#

[Updates in Jun 2023] 🎉A short version of the PyPOTS paper is accepted by the 9th SIGKDD international workshop on Mining and Learning from Time Series (MiLeTS’23). Besides, PyPOTS has been included as a PyTorch Ecosystem project.

PyPOTS paper is available on arXiv at this URL., and we are pursuing to publish it in prestigious academic venues, e.g. JMLR (track for Machine Learning Open Source Software). If you use PyPOTS in your work, please cite it as below and 🌟star PyPOTS repository to make others notice this library. 🤗

 1@article{du2023PyPOTS,
 2title={{PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series}},
 3author={Wenjie Du},
 4year={2023},
 5eprint={2305.18811},
 6archivePrefix={arXiv},
 7primaryClass={cs.LG},
 8url={https://arxiv.org/abs/2305.18811},
 9doi={10.48550/arXiv.2305.18811},
10}

or

Wenjie Du. (2023). PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series. arXiv, abs/2305.18811. https://doi.org/10.48550/arXiv.2305.18811

Research Projects Using PyPOTS#

There are scientific research projects using PyPOTS and referencing in their papers. Here is an incomplete list of them.

Project Milestones#

  • 2022-03: PyPOTS project is initiated;

  • 2022-04: PyPOTS v0.0.1 is released;

  • 2022-09: PyPOTS achieves its first 100 stars on GitHub;

  • 2023-03: PyPOTS is published on Conda-Forge, and users can install it via Anaconda;

  • 2023-04: PyPOTS website is launched, and PyPOTS achieves its first 10K downloads on PyPI;

  • 2023-05: PyPOTS v0.1 is released, and the preprint paper is published on arXiv;

  • 2023-06: A short version of PyPOTS paper is accepted by the 9th SIGKDD International Workshop on Mining and Learning from Time Series (MiLeTS’23);

  • 2023-07: PyPOTS has been accepted as a PyTorch Ecosystem project;