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~subject:"Deep learning"
~type_genre:"Arbeitspapier"
~type_genre:"Aufgabensammlung"
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A new efficient approximation scheme for solving high-dimensional semilinear PDEs : control variate method for Deep BSDE solver
Takahashi, Akihiko
;
Tsuchida, Yoshifumi
;
Yamada, Toshihiro
-
2021
-
This version : August 10, 2021
Persistent link: https://www.econbiz.de/10012616192
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2
A new efficient approximation scheme for solving high-dimensional semilinear PDEs : control variate method for Deep BSDE solver
Takahashi, Akihiko
;
Tsuchida, Yoshifumi
;
Yamada, Toshihiro
-
2021
Persistent link: https://www.econbiz.de/10012813680
Saved in:
3
A new efficient approximation scheme for solving high-dimensional semilinear PDEs : control variate method for Deep BSDE solver
Takahashi, Akihiko
;
Tsuchida, Yoshifumi
;
Yamada, Toshihiro
-
2021
-
Revised in August, November 2021, January and February 2022
Persistent link: https://www.econbiz.de/10013335002
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4
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
-
2021
Persistent link: https://www.econbiz.de/10013336341
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