KAR-HNN, an HNN built from univariate KAN blocks, shows mixed accuracy gains but fails to consistently reduce energy drift versus MLP-HNN.
On the representation of continuous functions of several variables by superposition of continuous functions of one variable and addition,
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Kolmogorov-Arnold Representation for Symplectic Learning: Advancing Hamiltonian Neural Networks
KAR-HNN, an HNN built from univariate KAN blocks, shows mixed accuracy gains but fails to consistently reduce energy drift versus MLP-HNN.