Approximations with deep neural networks in Sobolev time-space

23 December 2020

Papers citing "Approximations with deep neural networks in Sobolev time-space"

8 / 8 papers shown

Title
Deep Neural Network Framework Based on Backward Stochastic Differential Equations for Pricing and Hedging American Options in High Dimensions Yangang Chen J. Wan 41 61 0 25 Sep 2019
$Error bounds for approximations with deep ReLU neural networks in $W^{s,p}$ norms$ Error bounds for approximations with deep ReLU neural networks in $W^{s,p}$ norms Ingo Gühring Gitta Kutyniok P. Petersen 76 199 0 21 Feb 2019
A Survey of the Recent Architectures of Deep Convolutional Neural Networks Asifullah Khan A. Sohail Umme Zahoora Aqsa Saeed Qureshi OOD 93 2,291 0 17 Jan 2019
Neural Networks Trained to Solve Differential Equations Learn General Representations M. Magill F. Qureshi H. W. Haan 35 64 0 29 Jun 2018
The Deep Ritz method: A deep learning-based numerical algorithm for solving variational problems E. Weinan Ting Yu 113 1,380 0 30 Sep 2017
Optimal Approximation with Sparsely Connected Deep Neural Networks Helmut Bölcskei Philipp Grohs Gitta Kutyniok P. Petersen 162 256 0 04 May 2017
Why Deep Neural Networks for Function Approximation? Shiyu Liang R. Srikant 101 385 0 13 Oct 2016
Provable approximation properties for deep neural networks Uri Shaham A. Cloninger Ronald R. Coifman 123 230 0 24 Sep 2015