Tsururu: A Python-based Time Series Forecasting Strategies Library

Kostromina, Alina; Kuvshinova, Kseniia; Yugay, Aleksandr; Savchenko, Andrey; Simakov, Dmitry

doi:10.24963/ijcai.2025/1266

Tsururu: A Python-based Time Series Forecasting Strategies Library

Alina Kostromina, Kseniia Kuvshinova, Aleksandr Yugay, Andrey Savchenko, Dmitry Simakov

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Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence. Demo Track. Pages 11077-11081.

https://doi.org/10.24963/ijcai.2025/1266

Keywords

Data Mining: DM: Mining spatial and/or temporal data
Machine Learning: ML: Time series and data streams

Abstract

While current time series research focuses on developing new models, crucial questions of selecting an optimal approach for training such models are underexplored. Tsururu, a Python library introduced in this paper, bridges SoTA research and industry by enabling flexible combinations of global and multivariate approaches and multi-step-ahead forecasting strategies. It also enables seamless integration with various forecasting models. Available at https://github.com/sb-ai-lab/tsururu.

Alina Kostromina, Kseniia Kuvshinova, Aleksandr Yugay, Andrey Savchenko, and Dmitry Simakov. 2025. Tsururu: A Python-based Time Series Forecasting Strategies Library. In Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25. IJCAI, 11077–11081. https://doi.org/10.24963/ijcai.2025/1266

@inproceedings{ijcai2025p1266,
  title     = {Tsururu: A Python-based Time Series Forecasting Strategies Library},
  author    = {Kostromina, Alina and Kuvshinova, Kseniia and Yugay, Aleksandr and Savchenko, Andrey and Simakov, Dmitry},
  booktitle = {Proceedings of the Thirty-Fourth International Joint Conference on
               Artificial Intelligence, {IJCAI-25}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {James Kwok},
  pages     = {11077--11081},
  year      = {2025},
  month     = {8},
  note      = {Demo Track},
  doi       = {10.24963/ijcai.2025/1266},
  url       = {https://doi.org/10.24963/ijcai.2025/1266},
}

TY  - CPAPER
TI  - Tsururu: A Python-based Time Series Forecasting Strategies Library
AU  - Kostromina, Alina
AU  - Kuvshinova, Kseniia
AU  - Yugay, Aleksandr
AU  - Savchenko, Andrey
AU  - Simakov, Dmitry
T2  - Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-25
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2025
SP  - 11077
EP  - 11081
DO  - 10.24963/ijcai.2025/1266
UR  - https://doi.org/10.24963/ijcai.2025/1266
ER  -