<div align="center">
  
# Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization

[![preprint](https://img.shields.io/static/v1?label=arXiv&message=2412.05244&color=B31B1B&logo=arXiv)](https://arxiv.org/abs/2412.05244)
[![License: MIT](https://img.shields.io/badge/License-Apache--2.0-green.svg)](https://opensource.org/licenses/Apache-2.0)

</div>

> [!NOTE]  
> ~~Code coming soon~~. Code release for WaveToken has been deprioritized due to other engagements. If you are interested in a reference implementation of WaveToken, please open a discussion in this repo.

## 📝 Citation

If you find the code useful for your research, please consider citing the associated [paper](https://arxiv.org/abs/2412.05244):

```
@InProceedings{masserano2024enhancing,
  title={Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization},
  author={Masserano, Luca and Ansari, Abdul Fatir and Han, Boran and Zhang, Xiyuan and Faloutsos, Christos and Mahoney, Michael W and Wilson, Andrew Gordon and Park, Youngsuk and Rangapuram, Syama and Maddix, Danielle C and and Wang, Yuyang},
  booktitle = {Proceedings of the 40th International Conference on Machine Learning},
  year={2025}
}
```

## 🛡️ Security

See [CONTRIBUTING](CONTRIBUTING.md#security-issue-notifications) for more information.

## 📃 License

This project is licensed under the Apache-2.0 License.