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by yathaid
587 days ago
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Neural networks can encode any computable function. KANs have no advantage in terms of computability. Why are they a promising pathway? Also, the splines in KANs are no more "explainable" than the matrix weights. Sure, we can assign importance to a node, but so what? It has no more meaning than anything else. |
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