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The Kolmogorov-Arnold network originates from the Kolmogorov-Arnold representation theorem, placing learnable univariate functions (usually parameterized with B-splines) on the edges; in theory it can approximate complex functions with fewer parameters and is especially good at fitting smooth continuous mappings, but the engineering complexity of spline computation and parameter initialization is higher.
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10/15/2026
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