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Asymptotic Expansion and Weak Approximation : Applications of Malliavin Calculus and Deep Learning / / by Akihiko Takahashi, Toshihiro Yamada



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Autore: Takahashi Akihiko Visualizza persona
Titolo: Asymptotic Expansion and Weak Approximation : Applications of Malliavin Calculus and Deep Learning / / by Akihiko Takahashi, Toshihiro Yamada Visualizza cluster
Pubblicazione: Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025
Edizione: 1st ed. 2025.
Descrizione fisica: 1 online resource (177 pages)
Disciplina: 519.5
Soggetto topico: Statistics
Mathematical statistics - Data processing
Statistical Theory and Methods
Statistics and Computing
Applied Statistics
Probabilitats
Processos estocàstics
Soggetto genere / forma: Llibres electrònics
Altri autori: YamadaToshihiro  
Nota di contenuto: Chapter 1. Introduction -- Chapter 2. Itô calculus -- Chapter 3. Malliavin calculus -- Chapter 4. Asymptotic expansion -- Chapter 5. Weak approximation -- Chapter 6. Application: Deep learning-based weak approximation.
Sommario/riassunto: This book provides a self-contained lecture on a Malliavin calculus approach to asymptotic expansion and weak approximation of stochastic differential equations (SDEs), along with numerical methods for computing parabolic partial differential equations (PDEs). Constructions of weak approximation and asymptotic expansion are given in detail using Malliavin’s integration by parts with theoretical convergence analysis. Weak approximation algorithms and Python codes are available with numerical examples. Moreover, the weak approximation scheme is effectively applied to high-dimensional nonlinear problems without suffering from the curse of dimensionality through combining with a deep learning method. Readers including graduate-level students, researchers, and practitioners can understand both theoretical and applied aspects of recent developments of asymptotic expansion and weak approximation.
Titolo autorizzato: Asymptotic Expansion and Weak Approximation  Visualizza cluster
ISBN: 981-9682-80-0
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9911031564503321
Lo trovi qui: Univ. Federico II
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Serie: JSS Research Series in Statistics, . 2364-0065