The Rise of Diffusion Models in Time-Series Forecasting

This repository contains the complete LuaTeX source code and the final PDF of the literature survey, "The Rise of Diffusion Models in Time-Series Forecasting" authored by Caspar Meijer and Lydia Y. Chen. This comprehensive survey delves into the application of diffusion models in time-series forecasting, demonstrating state-of-the-art results in various fields of generative AI.

Contributors

• Caspar Meijer, EEMCS Distributed Systems, Delft University of Technology, c.j.meijer-1@student.tudelft.nl
• Lydia Y. Chen, EEMCS Distributed Systems, Delft University of Technology, lydiaychen@ieee.org

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Cite

If the work has helped you in your endevors, or you use any of the latex illustrations / figures:

@misc{meijer2024rise,
      title={The Rise of Diffusion Models in Time-Series Forecasting}, 
      author={Caspar Meijer and Lydia Y. Chen},
      year={2024},
      eprint={2401.03006},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}

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For any further questions or inquiries, please open an issue or contact Caspar directly.

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Shield:

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.