1 citations · 1 across the 3 of their papers we have counts for
3 papers
math.NA2024
Quantifying uncertainty in the numerical integration of evolution equations based on Bayesian isotonic regression
Yuto Miyatake, Kaoru Irie, Takeru Matsuda
This paper presents a new Bayesian framework for quantifying discretization errors in numerical solutions of ordinary differential equations. By modelling the errors as random vari…
math.ST2024
Minimaxity under the half-Cauchy prior
Yuzo Maruyama, Takeru Matsuda
This is a follow-up paper of Polson and Scott (2012, Bayesian Analysis), which claimed that the half-Cauchy prior is a sensible default prior for a scale parameter in hierarchical…
math.ST2023★ 1 cited
Minimaxity under half-Cauchy type priors
Yuzo Maruyama, Takeru Matsuda
This is a follow-up paper of Polson and Scott (2012, Bayesian Analysis), which claimed that the half-Cauchy prior is a sensible default prior for a scale parameter in hierarchical…