170 citations · 763 across the 30 of their papers we have counts for
5 papers · 1 filter
Multi-fidelity data fusion for the approximation of scalar functions with low intrinsic dimensionality through active subspaces
Francesco Romor, Marco Tezzele, Gianluigi Rozza
Gaussian processes are employed for non-parametric regression in a Bayesian setting. They generalize linear regression, embedding the inputs in a latent manifold inside an infinite…
Kernel-based active subspaces with application to computational fluid dynamics parametric problems using the discontinuous Galerkin method
Francesco Romor, Marco Tezzele, Andrea Lario +1
Nonlinear extensions to the active subspaces method have brought remarkable results for dimension reduction in the parameter space and response surface design. We further develop a…
On the comparison of LES data-driven reduced order approaches for hydroacoustic analysis
Mahmoud Gadalla, Marta Cianferra, Marco Tezzele +3
In this work, Dynamic Mode Decomposition (DMD) and Proper Orthogonal Decomposition (POD) methodologies are applied to hydroacoustic dataset computed using Large Eddy Simulation (LE…
A supervised learning approach involving active subspaces for an efficient genetic algorithm in high-dimensional optimization problems
Nicola Demo, Marco Tezzele, Gianluigi Rozza
In this work, we present an extension of the genetic algorithm (GA) which exploits the supervised learning technique called active subspaces (AS) to evolve the individuals on a low…
Enhancing CFD predictions in shape design problems by model and parameter space reduction
Marco Tezzele, Nicola Demo, Giovanni Stabile +2
In this work we present an advanced computational pipeline for the approximation and prediction of the lift coefficient of a parametrized airfoil profile. The non-intrusive reduced…