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I am writing to you regarding your outstanding work on the tsai project, which has been instrumental in maintaining state-of-the-art models for time series analysis. Your contributions to the field are highly appreciated and have been incredibly valuable to the community.
We recently presented our work at ICLR 2024 on a new model called TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting. This model leverages a decomposable multiscale mixing mechanism, achieving significant improvements in time series forecasting performance and demonstrating superior results across various benchmark tests.
Given the alignment of our work with the goals of the tsai project, we would be honored if you could assist us in adding the TimeMixer model to the tsai project. We believe that incorporating TimeMixer will further enhance the repository, providing the community with more options and stronger predictive capabilities.
If you have any questions or require additional technical details, please do not hesitate to reach out. We are more than willing to provide any necessary support and assistance.
Thank you very much for your consideration and support. We look forward to your positive response.
The text was updated successfully, but these errors were encountered:
@oguiza Hi, are we still maintaining and updating this project? I haven't received any feedback from you. If you see this message, please contact me at your convenience.
Dear Maintainer,
I hope this message finds you well.
I am writing to you regarding your outstanding work on the tsai project, which has been instrumental in maintaining state-of-the-art models for time series analysis. Your contributions to the field are highly appreciated and have been incredibly valuable to the community.
We recently presented our work at ICLR 2024 on a new model called TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting. This model leverages a decomposable multiscale mixing mechanism, achieving significant improvements in time series forecasting performance and demonstrating superior results across various benchmark tests.
Given the alignment of our work with the goals of the tsai project, we would be honored if you could assist us in adding the TimeMixer model to the tsai project. We believe that incorporating TimeMixer will further enhance the repository, providing the community with more options and stronger predictive capabilities.
The GitHub repository for TimeMixer can be found at the following link: https://github.com/kwuking/TimeMixer.
If you have any questions or require additional technical details, please do not hesitate to reach out. We are more than willing to provide any necessary support and assistance.
Thank you very much for your consideration and support. We look forward to your positive response.
The text was updated successfully, but these errors were encountered: