Hierarchical radial-basis-function Kolmogorov-Arnold networks are introduced with proofs of universal approximation for functions and random fields under Wasserstein-2 distance.
arXiv preprint arXiv:2511.13977 , year=
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Hierarchical RBF-KAN and RBF-SKAN Architectures for Multidimensional Function Approximation and Random Field Learning
Hierarchical radial-basis-function Kolmogorov-Arnold networks are introduced with proofs of universal approximation for functions and random fields under Wasserstein-2 distance.