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cs.LG2025
Expressivity of Quadratic Neural ODEs
Joshua Hanson, Maxim Raginsky
This work focuses on deriving quantitative approximation error bounds for neural ordinary differential equations having at most quadratic nonlinearities in the dynamics. The simple…
cs.LG2024
Function approximation by neural nets in the mean-field regime: Entropic regularization and controlled McKean-Vlasov dynamics
Belinda Tzen, Maxim Raginsky
We consider the problem of function approximation by two-layer neural nets with random weights that are "nearly Gaussian" in the sense of Kullback-Leibler divergence. Our setting i…