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What if instead of splines there were Fourier series or something like that? Would that be easier to infer and learn on GPU if it was somehow teachable?

EDIT: FourierKAN exists https://arxiv.org/html/2406.01034v1

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I'd expect Chebyshev polynomials to be much faster and easier to work with than splines, certainly, and probably Fourier series as well. (Especially if there aren't trig instructions in hardware, because then each sine or cosine is itself a chebyshev polynomial to evaluate).

Fourier subcomponents are definitely teachable in general. I'd expect that FourierKAN to have similar runtime to a normal KAN, only really benefitting from a GPU on datasets where you get better predictive performance than a normal KAN.

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