| --- |
| license: other |
| license_name: tsicl-v1-license-v1.0 |
| license_link: LICENSE |
| model_id: ts-icl |
| tags: |
| - time series |
| - foundation model |
| - time series imputation |
| - timeseries forecasting |
| pipeline_tag: time-series-forecasting |
| paper: https://arxiv.org/abs/2606.05878 |
| library_name: tsicl |
| --- |
| |
| # TS-ICL: A Flexible Time-Index Foundation Model for Time Series via In-Context Learning |
|
|
| ## Installation |
| ```bash |
| pip install tsicl |
| ``` |
|
|
| Source code available at [GitHub - EDF-Lab/ts-icl](https://github.com/EDF-Lab/ts-icl). |
|
|
| Example notebooks can be found at [GitHub - EDF-Lab/ts-icl/notebooks](https://github.com/EDF-Lab/ts-icl/tree/main/notebooks). |
|
|
| Check also the doc [here](https://edf-lab.github.io/ts-icl/). |
|
|
| ## License |
|
|
| TS-ICL weights and code are released under a non-commercial license, see [LICENSE](LICENSE). |
|
|
| ## Citation |
|
|
| If you use TS-ICL for research purposes, please consider citing the associated **[TS-ICL](https://arxiv.org/abs/2606.05878) paper**: |
|
|
| ```bibtex |
| @article{lenaour2026tsicl, |
| title={TS-ICL: A Flexible Time-Indexed Foundation Model for Time Series via In-Context Learning}, |
| author={Le Naour, Etienne and Nabil, Tahar and Petralia, Adrien}, |
| journal={arXiv preprint arXiv:2606.05878}, |
| year={2026} |
| } |
| ``` |
|
|
