Fabio Nobile

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

In this second article (Part II), we analyze the numerical algorithms for the Dynamical Low-Rank Approximation (DLRA) of Stochastic Differential Equations (SDEs) introduced in Part I arXiv:2601.21428 under the perspective of the stochastic discretization. Specifically, we employ...

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

Numerical simulations of high-dimensional stochastic differential equations (SDEs), which are increasingly employed in real-world applications, can be unaffordable in terms of computational time and memory. A possible solution is the deployment of reduced order methods (ROMs) tha...

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

In this second article (Part II), we analyze the numerical algorithms for the Dynamical Low-Rank Approximation (DLRA) of Stochastic Differential Equations (SDEs) introduced in Part I arXiv:2601.21428 under the perspective of the stochastic discretization. Specifically, we employ...

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

Numerical simulations of high-dimensional stochastic differential equations (SDEs), which are increasingly employed in real-world applications, can be unaffordable in terms of computational time and memory. A possible solution is the deployment of reduced order methods (ROMs) tha...