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I am working at timeseries forecasting, and I've using the PyTorch lib pytorch-forecasting lately. If you didn't know it, try it. It's great.

I am interested in SELU activation function for Self-Normalizing-Networks (SNNs, see, e.g., the docs). As I didn't find any N-Beats corrected to use SELU and its requirements (i.e. AlphaDropout, proper weights init), I made an implementation myself.

It would be great if any of you with experience with these concepts -NBeats architecture, pytorch-forecasting, or SELU()- could review whether everything is right in my implementation.

My implementation here: https://gist.github.com/pnmartinez/fef1f488497fa85a2cc1626af2a5b4bd

P. Navarro
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    I’m voting to close this question because code reviews are better suited in [codereview.stackexchange.com](https://codereview.stackexchange.com/). – Berriel Apr 16 '21 at 14:52
  • Hi @Berriel, you are right: you can find it [here](https://codereview.stackexchange.com/questions/259626/pytorch-forecasting-n-beats-model-with-selu-activation-function) – P. Navarro Apr 19 '21 at 08:22

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