On the rate of convergence of fully connected very deep neural network regression estimates

29 August 2019

Papers citing "On the rate of convergence of fully connected very deep neural network regression estimates"

10 / 10 papers shown

Title
How Neural Networks Learn the Support is an Implicit Regularization Effect of SGD Pierfrancesco Beneventano Andrea Pinto Tomaso A. Poggio MLT 32 1 0 17 Jun 2024
Soft Label PU Learning Puning Zhao Jintao Deng Xu Cheng 18 0 0 03 May 2024
Analysis of the expected $L_2$ error of an over-parametrized deep neural network estimate learned by gradient descent without regularization Selina Drews Michael Kohler 36 3 0 24 Nov 2023
Semiparametric Regression for Spatial Data via Deep Learning Kexuan Li Jun Zhu A. Ives V. Radeloff Fangfang Wang 28 8 0 10 Jan 2023
Precision Machine Learning Eric J. Michaud Ziming Liu Max Tegmark 24 34 0 24 Oct 2022
A Deep Generative Approach to Conditional Sampling Xingyu Zhou Yuling Jiao Jin Liu Jian Huang 10 41 0 19 Oct 2021
Convergence rates of deep ReLU networks for multiclass classification Thijs Bos Johannes Schmidt-Hieber 24 22 0 02 Aug 2021
Calibrating multi-dimensional complex ODE from noisy data via deep neural networks Kexuan Li Fangfang Wang Ruiqi Liu Fan Yang Zuofeng Shang 29 7 0 07 Jun 2021
Layer Sparsity in Neural Networks Mohamed Hebiri Johannes Lederer 36 10 0 28 Jun 2020
On Deep Instrumental Variables Estimate Ruiqi Liu Zuofeng Shang Guang Cheng 26 26 0 30 Apr 2020