66 citations · 124 across the 22 of their papers we have counts for
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math.ST2022★ 4 cited
Analysis of the rate of convergence of an over-parametrized deep neural network estimate learned by gradient descent
Michael Kohler, Adam Krzyzak
Estimation of a regression function from independent and identically distributed random variables is considered. The error with integration with respect to the design measure…
math.ST2022★ 2 cited
On the universal consistency of an over-parametrized deep neural network estimate learned by gradient descent
Selina Drews, Michael Kohler
Estimation of a multivariate regression function from independent and identically distributed data is considered. An estimate is defined which fits a deep neural network consisting…