Unbiased Deep Solvers for Linear Parametric PDEs-Reference-Cited by-同舟云学术

Unbiased Deep Solvers for Linear Parametric PDEs

Published:2021-07-04 Issue:4 Volume:28 Page:299-329
ISSN:1350-486X
Container-title:Applied Mathematical Finance
language:en
Short-container-title:Applied Mathematical Finance

Author:

Sabate Vidales Marc¹²,Šiška David²³,Szpruch Lukasz²⁴

Affiliation:

1. Edinburgh Parallel Computing Centre, University of Edinburgh, London, UK

2. School of Mathematics, University of Edinburgh, Edinburgh, UK

3. Vega Protocol

4. The Alan Turing Institute, London, UK

Funder

Alan Turing Institute

Publisher

Informa UK Limited

Subject

Applied Mathematics,Finance

Link

https://www.tandfonline.com/doi/pdf/10.1080/1350486X.2022.2030773

Reference51 articles.

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2. Beck C., S. Becker, P. Grohs, N. Jaafari, and A. Jentzen. 2018. “Solving Stochastic Differential Equations and Kolmogorov Equations by Means of Deep Learning.” arXiv:1806.00421.

3. Beck C., L. Gonon, and A. Jentzen. 2020. “Overcoming the Curse of Dimensionality in the Numerical Approximation of High-Dimensional Semilinear Elliptic Partial Differential Equations”.

4. Belomestny D., L. Iosipoi, and N. Zhivotovskiy. 2017. “Variance Reduction via Empirical Variance Minimization: Convergence and Complexity.” arXiv:1712.04667.

5. Variance reduction for discretised diffusions via regression

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