Toshihiro Yamada

28 papers Journal 27Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A deep learning-based forward scheme for forward-backward SDEs with jumps. J. Sci. Comput. Reiichiro Kawai, Riu Naito, Toshihiro Yamada
2026	J	`jnl`	Learning high-order weak approximation of SDEs by neural network with application to financial models. Oper. Res. Lett. Riu Naito, Toshihiro Yamada
2024	J	`jnl`	A forward scheme with machine learning for forward-backward SDEs with jumps by decoupling jumps. CoRR Reiichiro Kawai, Riu Naito, Toshihiro Yamada
2024	J	`jnl`	A weak approximation for Bismut's formula: An algorithmic differentiation method. Math. Comput. Simul. Naho Akiyama, Toshihiro Yamada
2024	J	`jnl`	An extended Milstein scheme for effective weak approximation of diffusions. CoRR Yuga Iguchi, Toshihiro Yamada
2024	J	`jnl`	Asymptotic Expansion and Weak Approximation for a Stochastic Control Problem on Path Space. Entropy Masaya Kannari, Riu Naito, Toshihiro Yamada
2023	J	`jnl`	Discrete Bismut formula: Conditional integration by parts and a representation for delta hedging process. Risk Decis. Anal. Naho Akiyama, Toshihiro Yamada
2023	J	`jnl`	New asymptotic expansion formula via Malliavin calculus and its application to rough differential equation driven by fractional Brownian motion. CoRR Akihiko Takahashi, Toshihiro Yamada
2023	J	`jnl`	Total variation bound for Milstein scheme without iterated integrals. Monte Carlo Methods Appl. Toshihiro Yamada
2022	—	`conf`	A deep learning-based high-order operator splitting method for high-dimensional nonlinear parabolic PDEs via Malliavin calculus: application to CVA computation. CIFEr Riu Naito, Toshihiro Yamada
2022	J	`jnl`	A high order weak approximation for jump-diffusions using Malliavin calculus and operator splitting. Monte Carlo Methods Appl. Naho Akiyama, Toshihiro Yamada
2022	J	`jnl`	A new efficient approximation scheme for solving high-dimensional semilinear PDEs: Control variate method for Deep BSDE solver. J. Comput. Phys. Akihiko Takahashi, Yoshifumi Tsuchida, Toshihiro Yamada
2022	J	`jnl`	Short Communication: A Gaussian Kusuoka Approximation without Solving Random ODEs. SIAM J. Financial Math. Toshihiro Yamada
2022	J	`jnl`	Weak approximation of SDEs for tempered distributions and applications. Adv. Comput. Math. Yuga Iguchi, Toshihiro Yamada
2021	J	`jnl`	A new efficient approximation scheme for solving high-dimensional semilinear PDEs: control variate method for Deep BSDE solver. CoRR Akihiko Takahashi, Yoshifumi Tsuchida, Toshihiro Yamada
2021	J	`jnl`	Acceleration of automatic differentiation of solutions to parabolic partial differential equations: a higher order discretization. Numer. Algorithms Kimiki Tokutome, Toshihiro Yamada
2021	J	`jnl`	High order weak approximation for irregular functionals of time-inhomogeneous SDEs. Monte Carlo Methods Appl. Toshihiro Yamada
2020	J	`jnl`	A machine learning solver for high-dimensional integrals: Solving Kolmogorov PDEs by stochastic weighted minimization and stochastic gradient descent through a high-order weak approximation scheme of SDEs with Malliavin weights. CoRR Riu Naito, Toshihiro Yamada
2019	J	`jnl`	A control variate method for weak approximation of SDEs via discretization of numerical error of asymptotic expansion. Monte Carlo Methods Appl. Yusuke Okano, Toshihiro Yamada
2019	J	`jnl`	A second-order discretization for forward-backward SDEs using local approximations with Malliavin calculus. Monte Carlo Methods Appl. Riu Naito, Toshihiro Yamada
2019	J	`jnl`	A third-order weak approximation of multidimensional Itô stochastic differential equations. Monte Carlo Methods Appl. Riu Naito, Toshihiro Yamada
2019	J	`jnl`	An Arbitrary High Order Weak Approximation of SDE and Malliavin Monte Carlo: Analysis of Probability Distribution Functions. SIAM J. Numer. Anal. Toshihiro Yamada
2019	J	`jnl`	Second Order Discretization of Bismut-Elworthy-Li Formula: Application to Sensitivity Analysis. SIAM/ASA J. Uncertain. Quantification Toshihiro Yamada, Kenta Yamamoto
2018	J	`jnl`	A second-order weak approximation of SDEs using a Markov chain without Lévy area simulation. Monte Carlo Methods Appl. Toshihiro Yamada, Kenta Yamamoto
2017	J	`jnl`	A higher order weak approximation scheme of multidimensional stochastic differential equations using Malliavin weights. J. Comput. Appl. Math. Toshihiro Yamada
2015	J	`jnl`	On Error Estimates for Asymptotic Expansions with Malliavin Weights: Application to Stochastic Volatility Model. Math. Oper. Res. Akihiko Takahashi, Toshihiro Yamada
2013	J	`jnl`	An asymptotic expansion formula for up-and-out barrier option price under stochastic volatility model. JSIAM Lett. Takashi Kato, Akihiko Takahashi, Toshihiro Yamada
2012	J	`jnl`	An Asymptotic Expansion with Push-Down of Malliavin Weights. SIAM J. Financial Math. Akihiko Takahashi, Toshihiro Yamada