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…