Extensions of the deep Galerkin method

DOI10.1016/j.amc.2022.127287OpenAlexW4281647640MaRDI QIDQ2148058

Yuri F. Saporito, Adolfo Correia, Ali Al-Aradi, Danilo de Freitas Naiff, Gabriel Jardim

Publication date: 21 June 2022

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1912.01455

zbMATH Keywords

neural networksstochastic controlHamilton-Jacobi-Bellman equationspartial differential equationspolicy improvementdeep Galerkin method

Mathematics Subject Classification ID

Stochastic analysis (60Hxx) Actuarial science and mathematical finance (91Gxx) Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems (65Mxx)

Related Items (4)

The deep parametric PDE method and applications to option pricing ⋮ Deep learning approximations for non-local nonlinear PDEs with Neumann boundary conditions ⋮ An overview on deep learning-based approximation methods for partial differential equations ⋮ An application of the splitting-up method for the computation of a neural network representation for the solution for the filtering equations

Uses Software

• DGM

Cites Work

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