J. Schmidt-Hieber

activity

20092026

most citedNonparametric regression using deep neural networks with ReLU activation function

292 citations · 770 across the 46 of their papers we have counts for

collaborators

Showing 2018 · math.STShow all

3 papers · 2 filters

math.ST2018

Nonparametric Bayesian analysis of the compound Poisson prior for support boundary recovery

Markus Reiss, Johannes Schmidt-Hieber

Given data from a Poisson point process with intensity $(x, y) \mapsto n 1 (f (x) \leq y),$ frequentist properties for the Bayesian reconstruction of the support boundary func…

math.ST2018

Posterior analysis of $n$ in the binomial $(n, p)$ problem with both parameters unknown -- with applications to quantitative nanoscopy

Johannes Schmidt-Hieber, Laura Fee Schneider, Thomas Staudt +3

Estimation of the population size $n$ from $k$ i.i.d.\ binomial observations with unknown success probability $p$ is relevant to a multitude of applications and has a long history.…

math.ST2018★ 2 cited

Asymptotic nonequivalence of density estimation and Gaussian white noise for small densities

Kolyan Ray, Johannes Schmidt-Hieber

It is well-known that density estimation on the unit interval is asymptotically equivalent to a Gaussian white noise experiment, provided the densities are sufficiently smooth and…

Nonparametric Bayesian analysis of the compound Poisson prior for support boundary recovery

Posterior analysis of n in the binomial (n,p) problem with both parameters unknown -- with applications to quantitative nanoscopy

Asymptotic nonequivalence of density estimation and Gaussian white noise for small densities

Posterior analysis of $n$ in the binomial $(n, p)$ problem with both parameters unknown -- with applications to quantitative nanoscopy