4 papers
LDDMM stochastic interpolants: an application to domain uncertainty quantification in hemodynamics
Sarah Katz, Francesco Romor, Jia-Jie Zhu +1
We introduce a novel conditional stochastic interpolant framework for generative modeling of three-dimensional shapes. The method builds on a recent LDDMM-based registration approa…
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…
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…
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…