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math.NA2026
Bayesian Inference of Discretization Error Means in ODEs via Ensemble Kalman Filtering
Shoji Toyota, Yuto Miyatake
We propose a Bayesian framework to quantify discretization errors in numerical solutions of ODE models based on observational data. The discretization error is modeled as a random…
math.OC2026
Accelerating SAV-based optimization via randomized low-rank Hessian approximation
Ryo Sagawa, Daisuke Furihata, Yuto Miyatake
We propose a new optimization method, the Nyström-enhanced relaxed scalar auxiliary variable method (N-RSAV), which incorporates curvature information into the RSAV framework to ac…
math.NA2026
An error control framework for computing the exponential of matrices arising from the finite element discretization
Fuminori Tatsuoka, Yuto Miyatake, Tomohiro Sogabe
Several methods for computing the action of the matrix exponential are expressed by substituting into a rational appro…