State-Space Kolmogorov-Arnold Networks fit a linear state-space model plus sparse learnable univariate functions, and the shapes of those functions recover the known cubic and saturation nonlinearities in two benchmark systems.
Decoupling Multivariate Polynomials for Nonlinear State-Space Models,
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State-Space Kolmogorov Arnold Networks for Interpretable Nonlinear System Identification
State-Space Kolmogorov-Arnold Networks fit a linear state-space model plus sparse learnable univariate functions, and the shapes of those functions recover the known cubic and saturation nonlinearities in two benchmark systems.