A deep learning approach to the probabilistic numerical solution of path-dependent partial differential equations

28 September 2022

Papers citing "A deep learning approach to the probabilistic numerical solution of path-dependent partial differential equations"

3 / 3 papers shown

Title
Multilevel Picard approximations and deep neural networks with ReLU, leaky ReLU, and softplus activation overcome the curse of dimensionality when approximating semilinear parabolic partial differential equations in $L^p$ -sense Ariel Neufeld Tuan Anh Nguyen 34 0 0 30 Sep 2024
Full error analysis of the random deep splitting method for nonlinear parabolic PDEs and PIDEs Ariel Neufeld Philipp Schmocker Sizhou Wu 34 7 0 08 May 2024
PDGM: a Neural Network Approach to Solve Path-Dependent Partial Differential Equations Yuri F. Saporito Zhao-qin Zhang 28 9 0 04 Mar 2020