期刊
MATHEMATICS AND COMPUTERS IN SIMULATION
卷 216, 期 -, 页码 386-396出版社
ELSEVIER
DOI: 10.1016/j.matcom.2023.09.003
关键词
Algorithmic differentiation; Stochastic differential equation; Weak approximation; Bismut formula; Gaussian kusuoka-approximation; Enlarged semigroup
The paper presents a novel algorithmic differentiation method using a weak approximation of the Bismut formula. It introduces a new operator splitting method based on Gaussian Kusuoka approximation for an enlarged semigroup that describes the differentiation of diffusion semigroup. The effectiveness of the new algorithmic differentiation is demonstrated through numerical examples.
The paper provides a novel algorithmic differentiation method by constructing a weak approximation for Bismut's formula. A new operator splitting method based on Gaussian Kusuoka-approximation is introduced for an enlarged semigroup describing differentiation of diffusion semigroup. The effectiveness of the new algorithmic differentiation is checked through numerical examples. (c) 2023 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.
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