Combinatorial relaxation algorithm for the entire sequence of the maximum degree of minors in mixed polynomial matrices. - Shun Sato 001 (JSIAM Lett., 2015)

An analysis on the asymptotic behavior of multistep linearly implicit schemes for the Duffing equation. - Shun Sato 001; Takayasu Matsuo; Daisuke Furihata (JSIAM Lett., 2015)

A Lyapunov-Type Theorem for Dissipative Numerical Integrators with Adaptive Time-Stepping. - Shun Sato 001; Takayasu Matsuo; Hideyuki Suzuki; Daisuke Furihata (SIAM J. Numer. Anal., 2015)

A novel discrete variational derivative method using "average-difference methods". - Daisuke Furihata; Shun Sato 001; Takayasu Matsuo (JSIAM Lett., 2016)

Combinatorial Relaxation Algorithm for the Entire Sequence of the Maximum Degree of Minors. - Shun Sato 001 (Algorithmica, 2017)

Constructing invariant-preserving numerical schemes based on Poisson and Nambu brackets. - Yuya Sugibuchi; Takayasu Matsuo; Shun Sato 001 (JSIAM Lett., 2018)

On spatial discretization of evolutionary differential equations on the periodic domain with a mixed derivative. - Shun Sato 001; Takayasu Matsuo (J. Comput. Appl. Math., 2019)

A robust numerical integrator for the short pulse equation near criticality. - Shun Sato 001; K. Oguma; Takayasu Matsuo; Bao-Feng Feng (J. Comput. Appl. Math., 2019)

Making Bidirected Graphs Strongly Connected. - Tatsuya Matsuoka; Shun Sato 001 (Algorithmica, 2020)

Linearly implicit structure-preserving schemes for Hamiltonian systems. - Sølve Eidnes; Lu Li; Shun Sato 001 (J. Comput. Appl. Math., 2021)

Mathematical analysis of a conservative numerical scheme for the Ostrovsky equation. - Shuto Kawai; Shun Sato 001; Takayasu Matsuo (JSIAM Lett., 2022)

Deriving efficient optimization methods based on stable explicit numerical methods. - Kansei Ushiyama; Shun Sato 001; Takayasu Matsuo (JSIAM Lett., 2022)

Essential convergence rate of ordinary differential equations appearing in optimization. - Kansei Ushiyama; Shun Sato 001; Takayasu Matsuo (JSIAM Lett., 2022)

A Unified Discretization Framework for Differential Equation Approach with Lyapunov Arguments for Convex Optimization. - Kansei Ushiyama; Shun Sato 001; Takayasu Matsuo (NeurIPS, 2023)

A new unified framework for designing convex optimization methods with prescribed theoretical convergence estimates: A numerical analysis approach. - Kansei Ushiyama; Shun Sato 001; Takayasu Matsuo (CoRR, 2023)

Mathematical analysis and numerical comparison of energy-conservative schemes for the Zakharov equations. - Shuto Kawai; Shun Sato 001; Takayasu Matsuo (CoRR, 2024)

A novel interpretation of Nesterov's acceleration via variable step-size linear multistep methods. - Ryota Nozawa; Shun Sato 001; Takayasu Matsuo (CoRR, 2024)

Analysis of nonquadratic energy-conservative schemes for KdV type-equations. - Shuto Kawai; Shun Sato 001; Takayasu Matsuo (CoRR, 2024)

Affine-invariant projection methods for conservative integration of differential equations. - Naoki Ishii; Shun Sato 001; Takayasu Matsuo (JSIAM Lett., 2024)

Analysis of continuous dynamical system models with Hessians derived from optimization methods. - Tomoya Kamijima; Shun Sato 001; Kansei Ushiyama; Takayasu Matsuo; Ken'ichiro Tanaka (JSIAM Lett., 2024)

High-order linearly implicit exponential integrators conserving quadratic invariants with application to scalar auxiliary variable approach. - Shun Sato 001 (Numer. Algorithms, 2024)

Properties and practicability of convergence-guaranteed optimization methods derived from weak discrete gradients. - Kansei Ushiyama; Shun Sato 001; Takayasu Matsuo (Numer. Algorithms, 2024)

Correction to: High-order linearly implicit exponential integrators conserving quadratic invariants with application to scalar auxiliary variable approach. - Shun Sato 001 (Numer. Algorithms, 2024)

A discrete variational derivative method for the Cahn-Hilliard equation with high-order spatial accuracy. - Kota Umezu; Shun Sato 001; Takayasu Matsuo (JSIAM Lett., 2025)