Feature/kan experiment

[marcopeix]

Add KAN model
Benchmark of KAN on M3 and M4 dataset against MLP and NBEATS

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[AzulGarza]

very cool @marcopeix, i left a couple of comments. also i think it might be pretty awesome to release the Auto version as well. perhaps in a different pr, once this one is merged.

[elephaint]

Cool!

• I think we should also add an AutoKANLinear model in models.ipynb, I think users will like the ability to have it auto-optimize when they are playing with the architecture. You can just copy-paste most of the code from a comparable MLP-based architecture and change the names.
• I think KANLinear should also be added to models.py and evaluation.py in action_files/test_models/src

[cchallu]

@marcopeix we also need to add KAN to the evaluation pipeline in https://github.com/Nixtla/neuralforecast/tree/main/action_files. You can check with Olivier how to add it,

[elephaint]

Looks good, @marcopeix!

[marcopeix]

@cchallu I already added KAN to the evaluation pipeline in action_files. Olivier checked it and says it's good! Let me know if I am missing something!

[marcopeix]

This PR is getting pretty big. Is it possible to review it and merge it soon? @cchallu @AzulGarza. Thanks! 😄

[candalfigomoro]

@marcopeix Convolutional KAN could also be considered, see: https://github.com/IvanDrokin/torch-conv-kan

[elephaint]

Awesome! Maybe also here we need to clear the outputs of the notebook of the models.

[elephaint]

Nice

Changes have already been addressed, PR can be merged