A new MOX Report entitled “PDE-regularised spatial quantile regression” by Castiglione, C.; Arnone, E.; Bernardi, M.; Farcomeni, A.; Sangalli, L.M. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/98-2024.pdf Abstract: We consider the problem of estimating the conditional quantiles of an unknown distribution from data gathered on […]
We are pleased to announce the successful conclusion of the Mathematics for Planet Earth workshop, held on 11–12 November at the Politecnico di Milano. With around 80 participants and 15 research posters, the event highlighted the transformative role of mathematics in understanding and addressing the challenges confronting our planet. The […]
Stefano Pagani, a researcher at the MOX Laboratory for Modeling and Scientific Computing in the Department of Mathematics at Politecnico di Milano, contributed to the third episode, “Building the Cities of Tomorrow,” of the podcast series The Sustainable Future. In his talk, Stefano Pagani explained how mathematical models and methods […]
A new MOX Report entitled “Neural networks based surrogate modeling for efficient uncertainty quantification and calibration of MEMS accelerometers” by Zacchei, F.; Rizzini, F.; Gattere, G.; Frangi, A.; Manzoni, A. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/95-2024.pdf Abstract: This paper addresses the computational challenges inherent […]
A new MOX Report entitled “PTPI-DL-ROMs: Pre-trained physics-informed deep learning-based reduced order models for nonlinear parametrized PDEs” by Brivio, S.; Fresca, S.; Manzoni, A. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/96-2024.pdf Abstract: Among several recently proposed data-driven Reduced Order Models (ROMs), the coupling of Proper […]
A new MOX Report entitled “Designing novel vascular stents with enhanced mechanical behavior through topology optimization of existing devices” by Ferro, N.; Mezzadri, F.; Carbonaro, D.; Galligani, E.; Gallo, D.; Morbiducci, U.; Chiastra, C.; Perotto, S. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/97-2024.pdf Abstract: A […]
A new MOX Report entitled “Multi-fidelity reduced-order surrogate modelling” by Conti, P.; Guo, M.; Manzoni, A.; Frangi, A.; Brunton, S. L.; Kutz, J.N. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/83-2024.pdf Abstract: High-fidelity numerical simulations of partial differential equations (PDEs) given a restricted computational budget can […]
A new MOX Report entitled “EKF-SINDy: Empowering the extended Kalman filter with sparse identification of nonlinear dynamics” by Rosafalco, L.; Conti, P.; Manzoni, A.; Mariani, S.; Frangi, A. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/82-2024.pdf Abstract: Measured data from a dynamical system can be assimilated […]
A new MOX Report entitled “Error estimates for POD-DL-ROMs: a deep learning framework for reduced order modeling of nonlinear parametrized PDEs enhanced by proper orthogonal decomposition” by Brivio, S.; Franco, Nicola R.; Fresca, S.; Manzoni, A. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/85-2024.pdf Abstract: POD-DL-ROMs […]
A new MOX Report entitled “On the latent dimension of deep autoencoders for reduced order modeling of PDEs parametrized by random fields” by Franco, N.R.; Fraulin, D.; Manzoni, A.; Zunino, P. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/86-2024.pdf Abstract: Deep Learning is having a remarkable […]