Asymptotic Expansion and Weak Approximation : Applications of Malliavin Calculus and Deep Learning (Springerbriefs in Statistics) / Takahashi, Akihiko/ Yamada, Toshihiro

髙橋明彦・山田俊皓（共）著／漸近展開と弱い近似：マリアバン解析の応用と深層学習<br>Asymptotic Expansion and Weak Approximation : Applications of Malliavin Calculus and Deep Learning (Springerbriefs in Statistics)

髙橋明彦・山田俊皓（共）著／漸近展開と弱い近似：マリアバン解析の応用と深層学習
Asymptotic Expansion and Weak Approximation : Applications of Malliavin Calculus and Deep Learning (Springerbriefs in Statistics)

Takahashi, Akihiko/ Yamada, Toshihiro

Springer Nature Switzerland AG（2025/08発売）

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製本 Paperback:紙装版/ペーパーバック版／ページ数 120 p.
言語 ENG
商品コード 9789819682799

Full Description

mso-bidi-language: AR-SA;">This book provides a self-contained lecture on a Malliavin calculus approach to asymptotic expansion and weak approximation of stochastic differential equations (SDEs) as well as numerical methods for computing parabolic partial differential equations (PDEs).