Sparse Bayesian KANs with spike-and-slab priors achieve near-minimax posterior contraction rates in anisotropic Besov spaces that adapt to unknown smoothness while keeping network depth fixed.
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Posterior Contraction Rates for Sparse Kolmogorov-Arnold Networks in Anisotropic Besov Spaces
Sparse Bayesian KANs with spike-and-slab priors achieve near-minimax posterior contraction rates in anisotropic Besov spaces that adapt to unknown smoothness while keeping network depth fixed.