A new MOX Report entitled “HypeMARL: Multi-Agent Reinforcement Learning For High-Dimensional, Parametric, and Distributed Systems” by Botteghi, N; Tomasetto, M; Fasel, U; Braghin, F; Manzoni, A has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/75-2026.pdf Abstract: Deep reinforcement learning has recently emerged as a promising feedback control […]
MOXlab
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A new MOX Report entitled “Learning PDE solution operators with variable initial conditions via Latent Dynamics Networks” by Pizzamiglio, S.M.; Pagani, S.; Regazzoni, F. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/76-2026.pdf Abstract: In many-query scenarios, data-driven surrogate models provide an efficient alternative to high-fidelity solvers […]
A new MOX Report entitled “Deep Symmetric Autoencoders from the Eckart-Young-Schmidt Perspective” by Brivio, S.; Franco, N. R. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/74-2026.pdf Abstract: Deep autoencoders have become a fundamental tool in various machine learning applications, ranging from dimensionality reduction and reduced order […]
A new MOX Report entitled “A weighted polygonal discontinuous Galerkin method for hierarchically coupled reaction–diffusion systems with cubic interactions” by Corti, M. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/73-2026.pdf Abstract: We develop and analyse a symmetric weighted interior penalty polytopal discontinuous Galerkin (SWIP-PolyDG) method for […]
A new MOX Report entitled “Optimal Transport Dropout for Structured Predictive Uncertainty” by Lorenzon, G.; Regazzoni, F. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/72-2026.pdf Abstract: Deterministic neural networks and neural operators provide point predictions with no intrinsic measure of reliability. Yet, predictive uncertainty may stem […]
A new MOX Report entitled “A mathematical model for irreversible damage of the collagen scaffold in the myocardium” by Radisic, I.; 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/71-2026.pdf Abstract: We propose a dissipative, irreversible damage model for anisotropic media […]
A new MOX Report entitled “Longitudinal versus quasi-P waves in weakly anisotropic elasticity: operator comparison and long-time dephasing” by Micheletti, S. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/70-2026.pdf Abstract: In isotropic elasticity, P-wave displacement is longitudinal and curl-free. In anisotropic elasticity, the physical quasi-P (qP) […]
At the International Festival of Engineering 2026 (Sep 18-20, 2026), the MOX Lab, Department of Mathematics, Politecnico di Milano, contributed with “Guida il gruppo, accendi il movimento!”: an interactive activity for both children and adults to explore the role of mathematics and computational modeling in describing how individual choices influence […]
Organizers: Paola F. Antonietti, Francesca Bonizzoni, Ivan Fumagalli, Niteen Kumar, Stefano Pagani When: 2027-8-30 – 2027-9-3 Where: Lake Como School of Advanced Studies, Villa del Grumello Description: Computational neurology aims to support neurologists by developing physics-based and data-driven models of the human central nervous system under both physiological and pathological […]
A new MOX Report entitled “Complexity-controlled QUBO formulation for topology optimization via anisotropic mesh adaptation” by Zecchi, A. A.; Ferro, N.; Perotto, S. has appeared in the MOX Report Collection. Check it out here: https://www.mate.polimi.it/biblioteca/add/qmox/69-2026.pdf Abstract: QUBO formulation provides a natural route to address topology optimization of continuum structures with […]