5 citations · 6 across the 4 of their papers we have counts for
3 papers · 1 filter
POD-CNF: reduced order modeling of parametrized stochastic PDEs via normalizing flows and proper orthogonal decomposition
Andrea Violante, Nicola Rares Franco, Andrea Manzoni
Reduced-order models (ROMs) learned from trusted numerical simulations enable the real-time simulation of complex physical systems, making computationally prohibitive tasks-such as…
Deep orthogonal decomposition: a continuously adaptive data-driven approach to model order reduction
Nicola Rares Franco, Andrea Manzoni, Paolo Zunino +1
We develop a novel deep learning technique, termed Deep Orthogonal Decomposition (DOD), for dimensionality reduction and reduced order modeling of parameter dependent partial diffe…
Nonlinear model order reduction for problems with microstructure using mesh informed neural networks
Piermario Vitullo, Alessio Colombo, Nicola Rares Franco +2
Many applications in computational physics involve approximating problems with microstructure, characterized by multiple spatial scales in their data. However, these numerical solu…