Johannes Schmidt-Hieber

15 catalog papers. Identity-linked publications and additional name matches are distinguished below.

ORCID: 0000-0003-2699-4990

University of Twente Drienerlolaan 5 , 7522 NB Enschede , The Netherlands

Publications

• Asymptotics of Stochastic Gradient Descent with Dropout Regularization in Linear Models — Journal of Machine Learning Research 2026 (name-matched, not ORCID-linked)
• Poorbita Kundu’s and Johannes Schmidt-Hieber’s contribution to the Discussion of 'Statistical exploration of the Manifold Hypothesis' by Whiteley et al — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2026 (name-matched, not ORCID-linked)
• Correction to “Nonparametric regression using deep neural networks with ReLU activation function” — The Annals of Statistics 2024
• Dropout Regularization Versus l2-Penalization in the Linear Model — Journal of Machine Learning Research 2024 (name-matched, not ORCID-linked)
• Johannes Schmidt-Hieber’s contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning’ — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2024
• Posterior Contraction for Deep Gaussian Process Priors — Journal of Machine Learning Research 2023 (name-matched, not ORCID-linked)
• On lower bounds for the bias-variance trade-off — The Annals of Statistics 2023
• Posterior analysis of n in the binomial (n,p) problem with both parameters unknown—with applications to quantitative nanoscopy — The Annals of Statistics 2021
• Nonparametric Bayesian analysis of the compound Poisson prior for support boundary recovery — The Annals of Statistics 2020
• Rejoinder: “Nonparametric regression using deep neural networks with ReLU activation function” — The Annals of Statistics 2020
• Nonparametric regression using deep neural networks with ReLU activation function — The Annals of Statistics 2020 (name-matched, not ORCID-linked)
• On adaptive posterior concentration rates — The Annals of Statistics 2015
• Bayesian linear regression with sparse priors — The Annals of Statistics 2015
• Asymptotic equivalence for regression under fractional noise — The Annals of Statistics 2014
• Multiscale methods for shape constraints in deconvolution: Confidence statements for qualitative features — The Annals of Statistics 2013