Unbiased MLMC stochastic gradient-based optimization of Bayesian experimental designs. - Takashi Goda; Tomohiko Hironaka; Wataru Kitade (CoRR, 2020)

Multilevel Monte Carlo Estimation of the Expected Value of Sample Information. - Tomohiko Hironaka; Michael B. Giles; Takashi Goda; Howard Thom (SIAM/ASA J. Uncertain. Quantification, 2020)

Unbiased MLMC Stochastic Gradient-Based Optimization of Bayesian Experimental Designs. - Takashi Goda; Tomohiko Hironaka; Wataru Kitade; Adam Foster 001 (SIAM J. Sci. Comput., 2022)

Estimating nested expectations without inner conditional sampling and application to value of information analysis. - Tomohiko Hironaka; Takashi Goda (CoRR, 2023)

An efficient estimation of nested expectations without conditional sampling. - Tomohiko Hironaka; Takashi Goda (J. Comput. Appl. Math., 2023)