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Here are what I think are the main conclusions of the article:

""" ... the most significant factor controlling performance is just parameter count. """

""" No matter what I did, the most simple neural network was still outperforming the fanciest KAN-based model I tried. """

I suspected this was the case when I first heard about KANs. Its nice to see someone diving into a bit more, even if it is just anecdotal.





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