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cs.LG2022
Qualitative neural network approximation over R and C: Elementary proofs for analytic and polynomial activation
Josiah Park, Stephan Wojtowytsch
In this article, we prove approximation theorems in classes of deep and shallow neural networks with analytic activation functions by elementary arguments. We prove for both real a…
cs.LG2021
Neural Network Approximation of Refinable Functions
Ingrid Daubechies, Ronald DeVore, Nadav Dym +6
In the desire to quantify the success of neural networks in deep learning and other applications, there is a great interest in understanding which functions are efficiently approxi…