activity
20202022
most citedNeural-network learning of SPOD latent dynamics

32 citations · 55 across the 5 of their papers we have counts for

collaborators

5 papers

math.NA2022★ 1 cited

Non-intrusive reduced order models for the accurate prediction of bifurcating phenomena in compressible fluid dynamics

Niccolò Tonicello, Andrea Lario, Gianluigi Rozza +1

The present works is focused on studying bifurcating solutions in compressible fluid dynamics. On one side, the physics of the problem is thoroughly investigated using high-fidelit…

math.NA2022★ 4 cited

Deep learning-based reduced-order methods for fast transient dynamics

Martina Cracco, Giovanni Stabile, Andrea Lario +5

In recent years, large-scale numerical simulations played an essential role in estimating the effects of explosion events in urban environments, for the purpose of ensuring the sec…

math.NA2022

Reduced order modeling for spectral element methods: current developments in Nektar++ and further perspectives

Martin W. Hess, Andrea Lario, Gianmarco Mengaldo +1

In this paper, we present recent efforts to develop reduced order modeling (ROM) capabilities for spectral element methods (SEM). Namely, we detail the implementation of ROM for bo…

math.NA2021★ 32 cited

Neural-network learning of SPOD latent dynamics

Andrea Lario, Romit Maulik, Oliver T. Schmidt +2

We aim to reconstruct the latent space dynamics of high dimensional, quasi-stationary systems using model order reduction via the spectral proper orthogonal decomposition (SPOD). T…

math.NA2020★ 18 cited

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…