Direttore Vicario: Prof. Gabriele Grillo
Responsabile Gestionale: Dr.ssa Franca Di Censo


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Prossimi Seminari

  • Deep Learning meets Parametric Partial Differential Equations
    Gitta Kutyniok, Institute of Mathematics, Technische Universität Berlin (DE)
    giovedì 16 luglio 2020 alle ore 14:00, Online seminar:

Seminari Passati

  • Physics-Informed Neural Networks (PINNs): An alphabet of Algorithms for Diverse Applications
    George Karniadakis, Brown University (USA)
    giovedì 25 giugno 2020 alle ore 14:00 precise, Online seminar:
    We will present a new approach to develop a data-driven, learning-based framework for predicting outcomes of physical and biological systems and for discovering hidden physics from noisy data. We will introduce a deep learning approach based on neural networks (NNs) and generative adversarial networks (GANs). We also introduce new NNs that learn functionals and nonlinear operators from functions and corresponding responses for system identification. Unlike other approaches that rely on big data, here we “learn” from small data by exploiting the information provided by the physical conservation laws, which are used to obtain informative priors or regularize the neural networks. We will also make connections between Gauss Process Regression and NNs, and discuss the new powerful concept of meta-learning. We will demonstrate the power of PINNs for several inverse problems in fluid mechanics, solid mechanics and biomedicine including wake flows, shock tube problems, material characterization, brain aneurysms, etc, where traditional methods fail due to lack of boundary and initial conditions or material properties. There are many versions of PINNs, e.g., variational (VPINNs), stochastic (sPINNs), conservative (cPINNs), nonlocal (nPINNs), generalized (xPINNs), etc, and we will provide some highlights. In addition, we will present our recent theoretical results on the convergence and generation of PINNs.
  • Design and Health
    Stefano Capolongo , Politecnico di Milano
    mercoledì 18 marzo 2020 alle ore 12:15, aula B21
  • Comunicare la scienza: manuale di sopravvivenza
    Maurizio Melis , Giornalista scientifico
    mercoledì 11 marzo 2020 alle ore 12:15, aula B21
  • Bergman projections on pseudoconvex domains containing complex manifolds in their boundary
    Gian Maria Dall'Ara, School of Mathematics, University of Birmingham
    mercoledì 4 marzo 2020 alle ore 10:45, aula seminari - 3° piano
  • CANCELLED - this event has been cancelled
    Wolfgang Bangerth, Department of Mathematics, Campus Delivery, Fort Collins, CO, USA NUMETH-HPC
    venerdì 28 febbraio 2020 alle ore 14:00, Aula Saleri VI piano
  • Modeling and simulation of thermo-poroelastic processes in fractured geothermal reservoirs
    Eirik Keilegavlen, Department of Mathematics, University of Bergen, Norway
    giovedì 20 febbraio 2020 alle ore 11:30, Aula Saleri - VI piano
    We present a mathematical model for coupled thermo-hydro-mechanical processes in fractured porous media, motivated by applications to geothermal energy. The model is based on a mixed-dimensional representation of the host medium and fracture network. The dynamics in the host medium is governed by fully-coupled thermo-poroelasticity, while flow and energy transport can also take place in the fracture network. Fracture deformation, including opening and sliding, is modeled using techniques from contact mechanics. We present a finite volume approach for the mixed-dimensional model, combined with a primal-dual active set strategy for the contact problem.

  • Bail-in vs bail-out: Bank resolution and liability structure
    Alessandro Sbuelz, Università Cattolica (Milano)
    martedì 18 febbraio 2020 alle ore 12:00, Aula Consiglio
    What is the joint impact of different resolution regimes and capital requirements on the optimal liability structure of a bank holding insured deposits and issuing non-bailinable debt and bail-inable Tier1-capital debt? We address this novel question and find that: 1) a credible bail-in resolution regime rules out extreme leverage and creates value by postponing default; 2) a positive probability of bail-out destroys credibility with dramatic effects on financial risk-taking, to the point of reversing the classical positive link between optimal leverage and growth prospects; and 3) a strict enforcement of the Basel III CET1 capital requirement strongly mitigates the impact of a non-credible resolution regime.
  • Kalman Filters for PDEs, a new hope
    Philppe Moireau, INRIA et Ecole Polytechnique, Paris, France
    lunedì 17 febbraio 2020 alle ore 16:00, Aula Saleri, VI piano
    Kalman filters for PDEs is an old topic which is theoretically seducing but leads to a so-called curse of dimensionality in its numerical implementation. In order to circumvent this curse of dimensionality, it is now classical to base the numerical strategies on reduced order modeling. This raises the question of the accuracy of the resulting estimator.
    Alternatives approaches based on reduced-basis decomposition of the covariance were also developed in the past years, but here with an additional question of stability of the resulting estimator.
    Using H-matrix based discretization strategies, a recent numerical tool developed for integral equations discretization, we here show how a full Kalman estimator can now be envisioned PDE models and their associated large discretization, hence freshening up the interest for this old theory.