most citedA Streamline upwind Petrov-Galerkin Reduced Order Method for Advection-Dominated Partial Differential Equations under Optimal Control

10 citations · 13 across the 6 of their papers we have counts for

collaborators

9 papers

math.NA2026

Numerical Methods for Dynamical Low-Rank Approximations of Stochastic Differential Equations -- Part II: Stochastic discretization

Yoshihito Kazashi, Fabio Nobile, Fabio Zoccolan

This paper is the follow up (Part II) of arXiv:2601.21428, which proposed and analyzed time discretization schemes for the Dynamical Low-Rank Approximation (DLRA) of high-dimension…

math.NA2026

Existence of Dynamical Low-Rank Approximation for SDEs with Locally Lipschitz Coefficients

Yoshihito Kazashi, Fabio Nobile, Fabio Zoccolan

In this work, we consider the Dynamical Low Rank Approximation (DLRA) of a high-dimensional system of Stochastic Differential Equations (SDEs); DLRA is an effective reduced order m…

math.NA2026

Further Approaches of Dynamical Low-Rank Approximation for SDEs

Yoshihito Kazashi, Fabio Nobile, Fabio Zoccolan

In this article, we propose two other DLRA-type dynamics for stochastic differential equations (SDEs) than the one studied in arXiv:2308.11581, derived from a minimization of funct…

math.NA2026

Dynamical Low-Rank Smoothing

Youssef Marzouk, Fabio Nobile, Fabio Zoccolan

Computational costs often make smoothing procedures prohibitive for high-dimensional data assimilation problems. To address this challenge, we propose a dynamical low-rank approxim…

math.NA2026

Dynamical Low-Rank Filters for Data Assimilation

Yoshihito Kazashi, Youssef Marzouk, Fabio Nobile +1

We propose dynamical low-rank (DLRA) filters for data-assimilation problems based on stochastic differential equations (SDEs). We first consider a Kalman filter applied to a Euler-…

math.NA2026

Numerical Methods for Dynamical Low-Rank Approximations of Stochastic Differential Equations -- Part I: Time discretization

Yoshihito Kazashi, Fabio Nobile, Fabio Zoccolan

In this work (Part I), we study three time-discretization schemes for the Dynamical Low-Rank Approximation (DLRA) of high-dimensional stochastic differential equations (SDEs). Spec…

math.NA2023★ 3 cited

Dynamical Low-Rank Approximation for Stochastic Differential Equations

Yoshihito Kazashi, Fabio Nobile, Fabio Zoccolan

In this paper, we set the mathematical foundations of the Dynamical Low-Rank Approximation (DLRA) method for stochastic differential equations (SDEs). DLRA aims at approximating th…

math.NA2023

Stabilized Weighted Reduced Order Methods for Parametrized Advection-Dominated Optimal Control Problems governed by Partial Differential Equations with Random Inputs

Fabio Zoccolan, Maria Strazzullo, Gianluigi Rozza

In this work, we analyze Parametrized Advection-Dominated distributed Optimal Control Problems with random inputs in a Reduced Order Model (ROM) context. All the simulations are in…

math.NA2023★ 10 cited

A Streamline upwind Petrov-Galerkin Reduced Order Method for Advection-Dominated Partial Differential Equations under Optimal Control

Fabio Zoccolan, Maria Strazzullo, Gianluigi Rozza

In this paper we will consider distributed Linear-Quadratic Optimal Control Problems dealing with Advection-Diffusion PDEs for high values of the Péclet number. In this situation,…