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What does this PR do?

I have added an implementation of the SegRNN model along with testing examples. SegRNN is an innovative RNN-based model designed for Long-Term Time Series Forecasting (LTSF). It incorporates two fundamental strategies:

  1. Replacing point-wise iterations with segment-wise iterations.
  2. Substituting Recurrent Multi-step Forecasting (RMF) with Parallel Multi-step Forecasting (PMF).

I have made appropriate adjustments to the original SegRNN to make it suitable for imputation tasks.

Before submitting

  • This PR is made to fix a typo or improve the docs (you can dismiss the other checks if this is the case).
  • Was this discussed/approved via a GitHub issue? Please add a link to it if that's the case.
  • I have commented my code, particularly in hard-to-understand areas.
  • I have written necessary tests and already run them locally.

WenjieDu and others added 5 commits September 26, 2024 13:54
Update docs and release v0.8.1
Add FITS imputation model and update docs
* Add CSAI implementation to pypots

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Co-authored-by: Joseph Arul Raj Patterson Kulandai Raj <[email protected]>
Co-authored-by: LINGLONGQIAN <[email protected]>
Co-authored-by: Joseph Arul Raj Patterson Kulandai Raj <[email protected]>
@WenjieDu WenjieDu merged commit 1eecbbf into WenjieDu:dev Oct 15, 2024
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4 participants