Monthly Archives: September 2023

11 posts

New MOX Report on “HiPhome: HIgh order Projection-based HOMogEnisation for advection diffusion reaction problems”

A new MOX Report entitled “HiPhome: HIgh order Projection-based HOMogEnisation for advection diffusion reaction problems” by Conni, G.; Piccardo, S.; Perotto, S.; Porta, G.M.; Icardi, M. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/71-2023.pdf Abstract: We propose a new model reduction technique for multiscale scalar transport […]

New MOX Report on “Scaling survival analysis in healthcare with federated survival forests: A comparative study on heart failure and breast cancer genomics”

A new MOX Report entitled “Scaling survival analysis in healthcare with federated survival forests: A comparative study on heart failure and breast cancer genomics” by Archetti, A.; Ieva, F.; Matteucci, M. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/75-2023.pdf Abstract: Survival analysis is a fundamental tool […]

New MOX Report on “Ask Your Data—Supporting Data Science Processes by Combining AutoML and Conversational Interfaces”

A new MOX Report entitled “Ask Your Data—Supporting Data Science Processes by Combining AutoML and Conversational Interfaces” by Pidò, S.; Pinoli, P.; Crovari, P.; Ieva, F.; Garzotto, F.; Ceri, S. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/74-2023.pdf Abstract: Data Science is increasingly applied for solving […]

New MOX Report on “Nonlinear model order reduction for problems with microstructure using mesh informed neural networks”

A new MOX Report entitled “Nonlinear model order reduction for problems with microstructure using mesh informed neural networks” by Vitullo, P.; Colombo, A.; Franco, N.R.; Manzoni, A.; Zunino, P. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/68-2023.pdf Abstract: Many applications in computational physics involve approximating problems […]

New MOX Report on “Assessing the Impact of Hybrid Teaching on Students’ Academic Performance via Multilevel Propensity Score-based techniques”

A new MOX Report entitled “Assessing the Impact of Hybrid Teaching on Students’ Academic Performance via Multilevel Propensity Score-based techniques” by Ragni, A.; Ippolito, D.; Masci, C. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/70-2023.pdf Abstract: This study employs multilevel propensity score techniques in an innovative […]

Davide Riccobelli – Premio GADeS 2023

Il premio GADeS 2023 è stato assegnato dall’omonimo gruppo dell’AIMETA (Gruppo AIMETA di Dinamica e Stabilità) a Davide Riccobeli per miglior tesi di dottorato su temi di dinamica e stabilità con la seguente motivazione: “in recognition of the outstanding contribution in the mathematical modelling of soft and active bodies and […]

New MOX Report on “Reduced Lagrange multiplier approach for non-matching coupling of mixed-dimensional domains”

A new MOX Report entitled “Reduced Lagrange multiplier approach for non-matching coupling of mixed-dimensional domains” by Heltai, L.; Zunino, P. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/64-2023.pdf Abstract: Many physical problems involving heterogeneous spatial scales, such as the flow through fractured porous media, the study […]

New MOX Report on “A scalable well-balanced numerical scheme for the modelling of two-phase shallow granular landslide consolidation”

A new MOX Report entitled “A scalable well-balanced numerical scheme for the modelling of two-phase shallow granular landslide consolidation” by Gatti, F.; de Falco, C.; Perotto, S.; Formaggia, L.; Pastor, M. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/65-2023.pdf Abstract: We introduce a new method to […]

New MOX Report on “Deep learning-based reduced order models for the real-time simulation of the nonlinear dynamics of microstructures”

A new MOX Report entitled “Deep learning-based reduced order models for the real-time simulation of the nonlinear dynamics of microstructures” by Fresca, S.; Gobat, G.; Fedeli, P.; Frangi, A.; Manzoni, A. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/66-2023.pdf Abstract: We propose a non-intrusive Deep Learning-based […]