The paper “Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks,” signed by Francesco Regazzoni, Stefano Pagani, Matteo Salvador, Luca Dede’ and Alfio Quarteroni, has been published in the prestigious journal Nature Communications. The study concerns a new Operator Learning method in space-time, which allows non-intrusive learning of the […]
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A new MOX Report entitled “A Virtual Element method for non-Newtonian fluid flows” by Antonietti, P.F.; Beirao da Veiga, L.; Botti, M.; Vacca, G.; Verani, M. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/27-2024.pdf Abstract: In this paper, we design and analyze a Virtual Element discretization […]
A new MOX Report entitled “Robust radial basis function interpolation based on geodesic distance for the numerical coupling of multiphysics problems” by Bucelli, M.; Regazzoni, F.; Dede’, L.; Quarteroni, A. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/26-2024.pdf Abstract: Multiphysics simulations frequently require transferring solution fields […]
A new MOX Report entitled “Application of Deep Learning Reduced-Order Modeling for Single-Phase Flow in Faulted Porous Media” by Enrico Ballini e Luca Formaggia e Alessio Fumagalli e Anna Scotti e Paolo Zunino has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/25-2024.pdf Abstract: We apply reduced-order modeling […]
A new MOX Report entitled “A scalable well-balanced numerical scheme for a depth-integrated lava flow model” by Gatti, F.; de Falco, C.; Fois, M.; Formaggia, L. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/22-2024.pdf Abstract: We propose a scalable well-balanced numerical method to efficiently solve a […]
Alla guida del Laboratorio di Modellistica e Calcolo Scientifico MOX del Dipartimento di Matematica del Politecnico di Milano c’è la professoressa Paola Antonietti, principal investigator nel team che si è aggiudicato il Synergy Grant dell’ERC – Consiglio Europeo della Ricerca: un finanziamento pari a 7,8 milioni di euro per un periodo di sei anni. […]
A new MOX Report entitled “Discovering Artificial Viscosity Models for Discontinuous Galerkin Approximation of Conservation Laws using Physics-Informed Machine Learning” by Caldana, M.; Antonietti P. F.; Dede’ L. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/21-2024.pdf Abstract: Finite element-based high-order solvers of conservation laws offer large […]
A new MOX Report entitled “Structural health monitoring of civil structures: A diagnostic framework powered by deep metric learning” by Torzoni, M.; Manzoni, A.; Mariani, S. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/20-2024.pdf Abstract: Recent advances in learning systems and sensor technology have enabled powerful […]
A new MOX Report entitled “A multi-fidelity surrogate model for structural health monitoring exploiting model order reduction and artificial neural networks” by Torzoni, M.; Manzoni, A.; Mariani, S. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/19-2024.pdf Abstract: Stochastic approaches to structural health monitoring (SHM) are often […]
A new MOX Report entitled “A semi-conservative depth-averaged Material Point Method for fast flow-like landslides and mudflows” by Fois, M.; de Falco, C.; Formaggia, L. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/17-2024.pdf Abstract: We present a two-dimensional semi-conservative variant of the depth averaged material point […]