On the rate of convergence of fully connected deep neural network regression estimates M Kohler, S Langer The Annals of Statistics 49 (4), 2231-2249, 2021 | 116* | 2021 |
Approximating smooth functions by deep neural networks with sigmoid activation function S Langer Journal of Multivariate Analysis 182, 104696, 2021 | 73 | 2021 |
Estimation of a function of low local dimensionality by deep neural networks M Kohler, A Krzyżak, S Langer IEEE transactions on information theory 68 (6), 4032-4042, 2022 | 42 | 2022 |
Statistical theory for image classification using deep convolutional neural networks with cross-entropy loss M Kohler, S Langer arXiv preprint arXiv:2011.13602, 2020 | 23 | 2020 |
Analysis of the rate of convergence of fully connected deep neural network regression estimates with smooth activation function S Langer Journal of Multivariate Analysis 182, 104695, 2021 | 21 | 2021 |
Discussion of:“Nonparametric regression using deep neural networks with ReLU activation function” M Kohler, S Langer | 11 | 2020 |
The smoking gun: Statistical theory improves neural network estimates A Braun, M Kohler, S Langer, H Walk | 6 | 2021 |
Convergence rates for shallow neural networks learned by gradient descent A Braun, M Kohler, S Langer, H Walk Bernoulli 30 (1), 475-502, 2024 | 5 | 2024 |
Estimation of a regression function on a manifold by fully connected deep neural networks M Kohler, S Langer, U Reif Journal of Statistical Planning and Inference 222, 160-181, 2023 | 3 | 2023 |
A statistical analysis of an image classification problem S Langer, J Schmidt-Hieber arXiv preprint arXiv:2206.02151, 2022 | 2 | 2022 |
Supplement to “On the rate of convergence of fully connected deep neural network regression estimates.” M Kohler, S Langer | 2 | 2021 |
Dropout Regularization Versus -Penalization in the Linear Model G Clara, S Langer, J Schmidt-Hieber arXiv preprint arXiv:2306.10529, 2023 | | 2023 |
The Smoking Gun: Statistical Theory Improves Neural Network Estimates ABM Kohler, S Langer, H Walk | | 2021 |
Ein Beitrag zur statistischen Theorie des Deep Learnings S Langer | | 2020 |