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source:"econis"
~accessRights:"restricted"
~person:"Yamada, Toshihiro"
~person:"Ziogas, Andrew"
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Asymptotic expansion and deep neural networks overcome the curse of dimensionality in the numerical approximation of Kolmogorov partial differential equations with nonlinear coeffi...
Takahashi, Akihiko
;
Yamada, Toshihiro
-
2022
Persistent link: https://www.econbiz.de/10014266218
Saved in:
2
An acceleration scheme for deep learning-based BSDE solver using weak expansions
Naito, Riu
;
Yamada, Toshihiro
- In:
International journal of financial engineering
7
(
2020
)
2
,
pp. 1-12
Persistent link: https://www.econbiz.de/10012602946
Saved in:
3
A second-order discretization with Malliavin weight and Quasi-Monte Carlo method for option pricing
Yamada, Toshihiro
;
Yamamoto, Kenta
- In:
Quantitative finance
20
(
2020
)
11
,
pp. 1825-1837
Persistent link: https://www.econbiz.de/10012313518
Saved in:
4
An asymptotic expansion for forward-backward SDEs : a malliavin calculus approach
Takahashi, Akihiko
;
Yamada, Toshihiro
- In:
Asia-Pacific financial markets
23
(
2016
)
4
,
pp. 337-373
Persistent link: https://www.econbiz.de/10011619975
Saved in:
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