activity
20202026
most citedNon-linear manifold ROM with Convolutional Autoencoders and Reduced Over-Collocation method

9 citations · 12 across the 8 of their papers we have counts for

collaborators
Showing math.NAShow all

8 papers · 1 filter

math.NA2025

ROM for Viscous, Incompressible Flow in Polygons -- exponential -width bounds and convergence rate

Francesco Romor, Federico Pichi, Giovanni Stabile +2

We demonstrate exponential convergence of Reduced Order Model (ROM) approximations for mixed boundary value problems of the stationary, incompressible Navier-Stokes equations in pl…

math.NA2025

Efficient Numerical Strategies for Entropy-Regularized Semi-Discrete Optimal Transport

Moaad Khamlich, Francesco Romor, Gianluigi Rozza

Semi-discrete optimal transport (SOT), which maps a continuous probability measure to a discrete one, is a fundamental problem with wide-ranging applications. Entropic regularizati…

math.NA2025★ 1 cited

Data assimilation performed with robust shape registration and graph neural networks: application to aortic coarctation

Francesco Romor, Felipe Galarce, Jan Brüning +2

Image-based, patient-specific modelling of hemodynamics can improve diagnostic capabilities and provide complementary insights to better understand the hemodynamic treatment outcom…

math.NA2023

Generative Models for the Deformation of Industrial Shapes with Linear Geometric Constraints: model order and parameter space reductions

Guglielmo Padula, Francesco Romor, Giovanni Stabile +1

Real-world applications of computational fluid dynamics often involve the evaluation of quantities of interest for several distinct geometries that define the computational domain…

math.NA2023★ 2 cited

Explicable hyper-reduced order models on nonlinearly approximated solution manifolds of compressible and incompressible Navier-Stokes equations

Francesco Romor, Giovanni Stabile, Gianluigi Rozza

A slow decaying Kolmogorov n-width of the solution manifold of a parametric partial differential equation precludes the realization of efficient linear projection-based reduced-ord…

math.NA2023

Friedrichs' systems discretized with the Discontinuous Galerkin method: domain decomposable model order reduction and Graph Neural Networks approximating vanishing viscosity solutions

Francesco Romor, Davide Torlo, Gianluigi Rozza

Friedrichs' systems (FS) are symmetric positive linear systems of first-order partial differential equations (PDEs), which provide a unified framework for describing various ellipt…