Követés
Johannes Schmidt-Hieber
Johannes Schmidt-Hieber
E-mail megerősítve itt: utwente.nl
Cím
Hivatkozott rá
Hivatkozott rá
Év
Nonparametric regression using deep neural networks with ReLU activation function
J Schmidt-Hieber
7882020
Bayesian linear regression with sparse priors
I Castillo, J Schmidt-Hieber, A Van der Vaart
4302015
A comparison of deep networks with ReLU activation function and linear spline-type methods
K Eckle, J Schmidt-Hieber
Neural Networks 110, 232-242, 2019
3382019
Deep ReLU network approximation of functions on a manifold
J Schmidt-Hieber
arXiv preprint arXiv:1908.00695, 2019
972019
On adaptive posterior concentration rates
M Hoffmann, J Rousseau, J Schmidt-Hieber
862015
Conditions for posterior contraction in the sparse normal means problem
SL Van Der Pas, JB Salomond, J Schmidt-Hieber
672016
Multiscale methods for shape constraints in deconvolution: confidence statements for qualitative features
J Schmidt-Hieber, A Munk, L Dümbgen
592013
The Kolmogorov–Arnold representation theorem revisited
J Schmidt-Hieber
Neural networks 137, 119-126, 2021
562021
Nonparametric estimation of the volatility function in a high-frequency model corrupted by noise
A Munk, J Schmidt-Hieber
292010
Lower bounds for volatility estimation in microstructure noise models
A Munk, J Schmidt-Hieber
Borrowing Strength: Theory Powering Applications–A Festschrift for Lawrence …, 2010
282010
Adaptive wavelet estimation of the diffusion coefficient under additive error measurements
M Hoffmann, A Munk, J Schmidt-Hieber
Annales de l'IHP Probabilités et statistiques 48 (4), 1186-1216, 2012
252012
Convergence rates of deep ReLU networks for multiclass classification
T Bos, J Schmidt-Hieber
Electronic Journal of Statistics 16 (1), 2724-2773, 2022
232022
Sharp minimax estimation of the variance of Brownian motion corrupted with Gaussian noise
TT Cai, A Munk, J Schmidt-Hieber
Statistica Sinica, 1011-1024, 2010
202010
Minimax theory for a class of nonlinear statistical inverse problems
K Ray, J Schmidt-Hieber
Inverse Problems 32 (6), 065003, 2016
152016
Tests for qualitative features in the random coefficients model
F Dunker, K Eckle, K Proksch, J Schmidt-Hieber
142019
Rejoinder:“Nonparametric regression using deep neural networks with ReLU activation function”
J Schmidt-Hieber
132020
The Le Cam distance between density estimation, Poisson processes and Gaussian white noise
K Ray, J Schmidt-Hieber
Mathematical Statistics and Learning 1 (2), 101-170, 2018
132018
Asymptotic equivalence for regression under fractional noise
J Schmidt-Hieber
102014
Nonparametric estimation of the volatility under microstructure noise: wavelet adaptation
M Hoffmann, A Munk, J Schmidt-Hieber
Available at SSRN 1661906, 2010
102010
A regularity class for the roots of nonnegative functions
K Ray, J Schmidt-Hieber
Annali di Matematica Pura ed Applicata (1923-) 196, 2091-2103, 2017
92017
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Cikkek 1–20