170 citations · 763 across the 30 of their papers we have counts for
5 papers · 1 filter
A data-driven partitioned approach for the resolution of time-dependent optimal control problems with dynamic mode decomposition
Eleonora Donadini, Maria Strazzullo, Marco Tezzele +1
This work recasts time-dependent optimal control problems governed by partial differential equations in a Dynamic Mode Decomposition with control framework. Indeed, since the numer…
Multi-fidelity data fusion through parameter space reduction with applications to automotive engineering
Francesco Romor, Marco Tezzele, Markus Mrosek +2
Multi-fidelity models are of great importance due to their capability of fusing information coming from different numerical simulations, surrogates, and sensors. We focus on the ap…
A local approach to parameter space reduction for regression and classification tasks
Francesco Romor, Marco Tezzele, Gianluigi Rozza
Parameter space reduction has been proved to be a crucial tool to speed-up the execution of many numerical tasks such as optimization, inverse problems, sensitivity analysis, and s…
ATHENA: Advanced Techniques for High Dimensional Parameter Spaces to Enhance Numerical Analysis
Francesco Romor, Marco Tezzele, Gianluigi Rozza
ATHENA is an open source Python package for reduction in parameter space. It implements several advanced numerical analysis techniques such as Active Subspaces (AS), Kernel-based A…
Hull shape design optimization with parameter space and model reductions, and self-learning mesh morphing
Nicola Demo, Marco Tezzele, Andrea Mola +1
In the field of parametric partial differential equations, shape optimization represents a challenging problem due to the required computational resources. In this contribution, a…