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

  • Limit Theorems for the Fractional Non-homogeneous Poisson Process
    Enrico Scalas, University of Sussex
    martedì 16 aprile 2019 alle ore 14:30, Aula seminari del sesto piano
    The fractional non-homogeneous Poisson process was introduced by a time-change of the non-homogeneous Poisson process with the inverse ?-stable subordinator. We propose a similar definition for the (non-homogeneous) fractional compound Poisson process. We give both finite-dimensional and functional limit theorems for the fractional non-homogeneous Poisson process and the fractional compound Poisson process. The results are derived by using martingale methods, regular variation properties and Anscombe's theorem. Eventually, some of the limit results are verified in a Monte Carlo simulation.

    This is a joint work with Nikolai Leonenko and Mailan Trinh.
  • MATLAB Tools for Large-Scale Linear Inverse Problems
    James Nagy, Emory University
    lunedì 15 aprile 2019 alle ore 14:30, Aula Seminari 'Saleri' VI Piano MOX-Dipartimento di Matematica, Politecnico di Milano - Edificio 14
    Inverse Problems Inverse problems arise in a variety of applications: image processing, finance, mathematical biology, and more. Mathematical models for these applications may involve integral equations, partial differential equations, and dynamical systems, and solution schemes are formulated by applying algorithms that incorporate regularization techniques and/or statistical approaches. In most cases these solutions schemes involve the need to solve a large-scale ill-conditioned linear system that is corrupted by noise and other errors. In this talk we describe and demonstrate capabilities of a new MATLAB software package that consists of state-of-the-art iterative methods for solving such
    systems, which includes approaches that can automatically estimate regularization parameters, stopping iterations, etc., making them very simple to use. Thus, the package allows users to easily incorporate into their own applications (or simply experiment with) different iterative methods and regularization strategies with very little programming effort. On the other hand, sophisticated users can also easily access various options to tune the algorithms for certain applications. Moreover, the package includes several test problems and examples to illustrate how the iterative methods can be used on a variety of large-scale inverse problems.
    The talk will begin with a brief introduction to inverse problems, discuss considerations that are needed to compute an approximate solution, and describe some details about new efficient hybrid Krylov subspace methods that are implemented in our package. These methods can guide users in automatically choosing regularization parameters, and can be used to enforce various regularization schemes, such as sparsity. We will use imaging examples that arise in medicine and astronomy to illustrate the performance of the methods. This is joint work with Silvia Gazzola (University of Bath) and Per Christian Hansen (Technical University of Denmark).

  • Problemi di frontiera libera nelle scienze applicate
    Sandro Salsa, Politecnico di Milano
    mercoledì 10 aprile 2019 alle ore 12:15, Politecnico di Milano Campus Bonardi Edificio14 aula B21
  • Quantum Lévy Process on Lorentz-Lie algebra
    Ameur Dhahri, Politecnico di Milano
    mercoledì 10 aprile 2019 alle ore 11:30 precise, Aula Seminari III piano
    This is a joint work with Uwe Franz. We describe the construction of the quantum Levy process on Lorentz-Lie algebra.
  • How efficient surface representation can aid bio-molecular simulation
    Walter Rocchia, CONCEPT Lab – Istituto Italiano di Tecnologia, Genova
    martedì 9 aprile 2019 alle ore 11:30, Aula Seminari 'Saleri' VI Piano MOX-Dipartimento di Matematica, Politecnico di Milano - Edificio 14
    The progress of powerful experimental techniques such as Cryo--?Electron
    Microscopy represents a remarkable opportunity but also a significant challenge for computational techniques, which aim at extracting useful information and predicting the behavior of bio molecular systems. While pioneering attempts to perform molecular dynamics
    Simulation at this scale by means of super--?computers have been made, there still is the compelling need for enabling tools and approaches able to routinely analyze this kind
    of structures, identifying, for instance, interaction hot spots or new target regions for next generation drug discovery ....

  • On the modelling of particle and pedestrian motion with Fokker-Planck equations
    Alfio Borzì, University of Wuerzburg -Germania-
    giovedì 4 aprile 2019 alle ore 14:00, Aula Consiglio VII Piano - Edificio 14, Dipartimento di Matematica POLITECNICO DI MILANO
    Since the pioneering works of A. Einstein, M. von Smoluchowski, and P. Langevin, stochastic processes and the related Fokker-Planck equations have been used to model irregular motion in different situation. These equations are also considered to be adequate for modelling the motion of one pedestrian and of a crowd of people under certain circumstances. Therefore they can play a central role in the design of control strategies for different purposes as well as in the analysis and calibration of microscopic models of pedestrian interaction. The purpose of this talk is to review some mathematical results in this field, which includes different modelling issues concerning the optimal control of a single pedestrian subject to perturbation, the development of a new framework for pedestrians' avoidance dynamics based on the formulation of a Nash game, and a new approach to the analysis of superresolution 2D images of moving molecules on a cell membrane to obtain quantitative results on the organization of the membrane and on the interaction between the molecules.

    [1] M. Annunziato, A. Borzì, A Fokker-Planck control framework for stochastic systems, EMS Surveys In Mathematical Sciences, 5 (2018), 65-98.
    [2] M. Annunziato, A. Borzì, A Fokker-Planck control framework for multidimensional stochastic
    processes, Journal of Computational and Applied Mathematics, 237 (2013), 487-507.
    [3] S. Roy, A. Annunziato, A. Borzì, C. Klingenberg, A Fokker-Planck approach to control collective motion, Computational Optimization and Applications, 69 (2018), 423-459.
    [4] S. Roy, A. Annunziato, A. Borzì, A Fokker-Planck feedback control-constrained approach for modelling crowd motion, Journal of Computational and Theoretical Transport, 45 (2016), 442-458.
    [5] S. Roy, A. Borzì, A. Habbal, Pedestrian motion modelled by Fokker-Planck Nash games, Royal Society open science, 4, (2017) 170648-17.


  • Stima del valore aggiunto di scuola: stato dell'arte del modello INVALSI e prospettive. Quali implicazioni di policy?
    Tommaso Agasisti, Politecnico di Milano
    mercoledì 3 aprile 2019 alle ore 12:15, Politecnico di Milano Campus Bonardi Edificio14 aula B21
  • Simplicial splines for representation of density functions
    Karel Hron e Jitka Machalova, Palacky University di Olomouc
    martedì 2 aprile 2019 alle ore 15:00 precise, Aula Seminari 'Saleri' VI Piano MOX-Dipartimento di Matematica, Politecnico di Milano - Edificio 14
    In the context of functional data analysis, probability density functions as non-negative functions are characterized by specific properties of scale invariance and relative scale which enable to represent them with the unit integral constraint without loss of information. On the other hand, all these properties are a challenge when the densities need to be approximated with spline functions, including construction of the respective B-spline basis. The Bayes space methodology of density functions enables to express them as real functions in the standard L2 space using the clr transformation. The resulting functions possess the zero integral constraint. This is a key to propose a new B-spline basis, holding the same property, and consequently to build a new class of spline functions, called simplicial splines, which can approximate probability density functions in a consistent way. The contribution provides also construction of smoothing simplicial splines and possi!
    ble orthonormalization of the B-spline basis which might be useful in some applications. Finally, a concise analysis using simplicial splines is demonstrated with anthropometric data for the case of simplicial functional principal component analysis.