mlsanityData to 14 Oct 2026

Tsururu: A Python-based Time Series Forecasting Strategies Library

arXiv 2509.15843 ↗First posted 19 Sep 2025cs.LGcited by 2

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Abstract (arXiv)

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 .

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 16 of its 34 references that are in the map. First posted on arXiv 19 Sep 2025.

Builds on

16 of 34 references.

References · 16

  1. 2020Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecastingcited by 2,169
  2. 2022A Time Series is Worth 64 Words: Long-term Forecasting with Transformerscited by 2,039
  3. 2022Are Transformers Effective for Time Series Forecasting?cited by 1,424
  4. 2022TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysiscited by 1,058
  5. 2017DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networkscited by 1,013
  6. 2023One Fits All:Power General Time Series Analysis by Pretrained LMcited by 632
  7. 2024GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluationcited by 212
  8. 2024Deep Time Series Models: A Comprehensive Survey and Benchmarkcited by 197
  9. 2023Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysiscited by 117
  10. 2024CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patternscited by 106
  11. 2023The Capacity and Robustness Trade-off: Revisiting the Channel Independent Strategy for Multivariate Time Series Forecastingcited by 101
  12. 2021Darts: User-Friendly Modern Machine Learning for Time Seriescited by 91
4 more
  1. 2020Principles and Algorithms for Forecasting Groups of Time Series: Locality and Globalitycited by 70
  2. 2022Criteria for Classifying Forecasting Methodscited by 48
  3. 2022SketchBoost: Fast Gradient Boosted Decision Tree for Multioutput Problemscited by 6
  4. 2024Time-Series Classification for Dynamic Strategies in Multi-Step Forecastingcited by 5

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025HN-MVTS: HyperNetwork-based Multivariate Time Series Forecastingcited by 0
  2. 2026Chronax: A Jax Library for Forecasting and Conformal Inferencecited by 0