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Pisa Online Seminars - Constanza Rojas-Molina (Tuesday, April 27 at 16:00)
by Giacomo Filippo Di Gesu 21 Apr '21

21 Apr '21

Dear colleagues, I would like to invite you to the following online seminar organized by the Probability group of the University of Pisa. The talk will be accessible under the link Click here to join<https://teams.microsoft.com/l/meetup-join/19:af3d635091e049579e555a84219ab3…"Tid":"c7456b31-a220-47f5-be52-473828670aa1","Oid":"dfd1e5f6-331d-43e0-a180-4bb6ce727fb7"}> Best regards, Giacomo Tuesday, April 27, 16:00 Speaker: Constanza Rojas-Molina (CY Cergy Paris Université) Title: (Fractional) random Schrödinger operators, integrated density of states and localization Abstract: We consider the continuous Schrödinger operator - d^2/d^x^2 + B’(x) on the interval [0,L] where the potential B’ is a white noise. We study the entire spectrum of this operator in the large L limit. We prove the joint convergence of the eigenvalues and of the eigenvectors and describe the limiting shape of the eigenvectors for all energies. When the energy is much smaller than L, we find that we are in the localized phase and the eigenvalues are distributed as a Poisson point process. The transition towards delocalization holds for large eigenvalues of order L. In this regime, we show the convergence at the level of operators. The limiting operator in the delocalized phase is acting on R^2-valued functions and is of the form ``J \partial_t + 2*2 noise matrix'' (where J is the matrix ((0, -1)(1, 0))), a form appearing as a conjecture by Edelman Sutton (2006) for limiting random matrices. Joint works with Cyril Labbé. ************************ Giacomo Di Gesù Dipartimento di Matematica Università di Pisa Largo Bruno Pontecorvo 5 56127 - Pisa, Italy giacomo.digesu(a)unipi.it<mailto:giacomo.digesu@unipi.it> https://sites.google.com/site/giacomodigesu/

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(PMS)^2 online talk: Zdzislaw Brzezniak, Monday April 26 at 17:30
by Mario Maurelli 21 Apr '21

21 Apr '21

Dear colleagues, We are happy to announce the following online talk: Speaker: *Zdzislaw Brzezniak* (University of York, UK) Title: *The stochastic Strichartz estimates and stochastic nonlinear Schrödinger equations driven by Levy noise* Date and time: *Monday April 26, 17:30-18:30 (Rome time zone)* Abstract: see below Zoom link: https://us02web.zoom.us/j/87131794820?pwd=R3l0VEtpZXNzUmQ1bnlnbWhBUm5XQT09 Meeting ID: 871 3179 4820 Passcode: 5yFGwK This talk is the first of the *(PMS)^2: Pavia-Milano Seminar series on Probability and Mathematical Statistics* organized jointly by the universities Milano-Bicocca, Pavia, Milano-Politecnico and Milano-Statale. The series will run approximately every fortnight and, for the moment, will be held online. Participation is free and welcome! (though limited to 100 participants for technical reasons) Best regards The organizers (Mario Maurelli, Carlo Orrieri, Maurizia Rossi, Margherita Zanella) Abstract: We establish a new version of the stochastic Strichartz estimate for the stochastic convolution driven by jump noise which we apply to the stochastic nonlinear Schrodinger equation with nonlinear multiplicative jump noise in the Marcus canonical form. With the help of the deterministic Strichartz estimates, we prove the existence and uniqueness of a global solution to stochastic nonlinear Schrodinger equation in $L^2(R^n)$ with either focusing or defocusing nonlinearity in the full subcritical range of exponents as in the deterministic case. This talk will be based on a joint paper with Wei Liu and Jiahui Zhu.

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Seminar Pierre Alquier @Bocconi - April 22
by Giacomo Zanella 21 Apr '21

21 Apr '21

A reminder of the following BIDSA webinar (link <https://www.bidsa.unibocconi.eu/wps/wcm/connect/site/bidsa/home/news_events…> ): Date: Thursday, April 22, h14:00 (Italy time) Speaker: Pierre Alquier (RIKEN) Title: Robust Estimation via M.M.D. Minimization Abstract: In this talk, I will study the properties of parametric estimators based on the Maximum Mean Discrepancy (MMD) defined by Briol et al. (2019). In a first time, I will show that these estimators are universal in the i.i.d setting: even in case of misspecification, they converge to the best approximation of the distribution of the data in the model, without ANY assumption on this model. This leads to very strong robustness properties. In a second time,I will show that these results remain valid when the data is not independent, but satisfy instead a weak-dependence condition. This condition is based on a new dependence coefficient, which is itself defined thanks to the MMD. I will show through examples that this new notion of dependence is actually quite general. Reference: This talk is based on the following papers and softwares, with Badr-Eddine Chérief Abdellatif (Oxford University), Mathieu Gerber(University of Bristol), Jean-David Fermanian (ENSAE Paris) and Alexis Derumigny (University of Twente): http://arxiv.org/abs/1912.05737 http://proceedings.mlr.press/v118/cherief-abdellatif20a.html http://arxiv.org/abs/2006.00840 https://arxiv.org/abs/2010.00408 https://cran.r-project.org/web/packages/MMDCopula/ The webinar will be on zoom at: https://zoom.us/j/95795747882 Meeting ID: 957 9574 7882 Passcode: 025765 Kind regards, Giacomo Zanella

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(Reminder) Seminar Thursday 22 - Optimal constrained and unconstrained subgraph structures (prof. Clara Stegehuis)
by Gianmarco Bet 21 Apr '21

21 Apr '21

Dear colleagues, This is a reminder that tomorrow (Thursday 22) at 14:30, prof. Clara Stegehuis (Twente University) will give a virtual seminar “in Florence”, to which you are all invited. You can find title and abstract below this message. The seminar will be on Zoom. You can find the information to join below. If you know of someone who might be interested and is not subscribed to the random mailing list, please do not hesitate to forward this announcement to them. Kind regards, Gianmarco Topic: Clara Stegehuis - Optimal constrained and unconstrained subgraph structures Time: Apr 22, 2021 02:30 PM Rome Join Zoom Meeting https://us02web.zoom.us/j/85651690146?pwd=ZnRCbGR6OUlxM2J4RldJd2R1aVE3Zz09 <https://us02web.zoom.us/j/85651690146?pwd=ZnRCbGR6OUlxM2J4RldJd2R1aVE3Zz09> Meeting ID: 856 5169 0146 Passcode: 770134 Title: Optimal constrained and unconstrained subgraph structures Abstract: Subgraphs contain important information about network structures and their functions. We investigate the presence of subgraphs in a random graph model with infinite-variance degrees. We introduce an optimization problem which identifies the dominant structure of any given subgraph. The unique optimizer describes the degrees of the vertices that together span the most likely subgraph and allows us to count and characterize the asymptotic number of subgraphs in a simple manner. We then show that this optimization problem easily extends to investigating other random network structures, such as clustering, which expresses the probability that two neighbors of a vertex are connected. The optimization problem is able to find the behavior of network subgraphs in a wide class of random graph models. ---------------------------------------------------------------------- Gianmarco Bet (he/him) Junior researcher https://gianmarco.bet Phone: (+39) 055 2751491 Department of Mathematics and Informatics "U. Dini" University of Florence Viale Morgagni, 65 50134 Firenze, Italy Office 64 ----------------------------------------------------------------------

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Online seminar Svaluto-Ferro
by matteo.burzoni＠unimi.it 20 Apr '21

20 Apr '21

Dear colleagues, it is our pleasure to invite you to the following online seminar: Zoom link (see also details below): <https://us02web.zoom.us/j/88398874167?pwd=YkRzdlNYWjVjUlc3T294ZjZuVHNSdz09> https://us02web.zoom.us/j/88398874167?pwd=YkRzdlNYWjVjUlc3T294ZjZuVHNSdz09 Speaker: <https://homepage.univie.ac.at/sara.svaluto-ferro/> Sara Svaluto-Ferro (University of Vienna) Title: From signature-based models to affine and polynomial processes and back. Time: Tuesday, April 27, 4PM (Italian time) Abstract: Modern universal classes of dynamic processes, based on neural networks or signature methods, have recently entered the field of stochastic modeling, in particular in Mathematical Finance. This has opened the door to more data-driven and thus more robust model selection mechanisms, while principles like no arbitrage still apply. We analyze here different types of signature models. In the first part, we focus on models based on the signature of a supporting process, which can range from a Brownian motion, to a multidimensional Levy-process, to a general multidimensional tractable stochastic process, to the times series corresponding to some liquid objects on the market. We also present methods how to fit these models to data. In the second part we focus on signature SDEs, i.e. (possibly Lévy driven) SDEs whose characteristics are linear functions of the process signature. We show how these new models can be embedded in the framework of affine and polynomial processes, which have been - due to their tractability - the dominating process class prior to the new era of highly overparametrized dynamic models. We show that generic classes of diffusion models can be described in terms of a signature SDEs. This allows to get power series expansions for expected values of analytic functions of the process' marginals. The talk is based on joint works with Christa Cuchiero, Guido Gazzani, Francesca Primavera and Josef Teichmann. Zoom meeting details: meeting ID: 883 9887 4167 Passcode: mVJ6SR Best, Matteo Burzoni

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New deadline for BISP12 - Twelfth Workshop on Bayesian Inference in Stochastic Processes
by elisa varini 20 Apr '21

20 Apr '21

Having received some late submission requests, we decided to reopen the call for contributed papers until 25 April 2021. It is possible to submit abstracts (using the templates in the website) at https://bisp12.imati.cnr.it/ In the meantime, we have completed the list of invited speakers (all junior ones) and we are going to contact senior researchers who will serve as discussants. The speakers will be: • Atilla Ay (George Washington University, USA) • Clara Grazian (University of New South Wales, Australia) • Andrew Holbrook (University of California, Los Angeles, USA) • Kaoru Irie (University of Tokyo, Japan) • Roi Naveiro (CSIC-ICMAT, Spain) • Giovanni Rebaudo (University of Texas at Austin, USA) • Claudia Solis-Lemus (University of Wisconsin-Madison, USA) • Stéphanie Van Der Pas (Amsterdam UMC, The Netherlands) • Andi Wang (University of Bristol, UK) • Paul Wu (Queensland University of Technology, Australia) The titles of their contributions are available on the website. It is also possible to register (free of charge) on the same website to attend the workshop on 27-28 May (afternoons, Central European Summer Time). Elisa Varini and Fabrizio Ruggeri Chairs, Organising and Scientific Committees

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Richiesta di comunicazione ai membri della lista RANDOM
by Enrico Moretto 20 Apr '21

20 Apr '21

con preghiera di diffusione alla lista RANDOM. Ringrazio. Cordiali saluti, enrico moretto *** Si informano i colleghi interessati che il workshop "/Network models for financial contagion and systemic risk/", organizzato dal Dipartimento di Economia e Management dell'Università di Pavia si terrà online il prossimo 28 maggio 2021. I contributi selezionati saranno considerati per la special issue "Network models for financial contagion and systemic risk" della rivista Frontiers in AI (https://www.frontiersin.org/research-topics/17785/network-models-for-financ… <https://eur01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.front…>). La scadenza della call for paper è fissata per il 14 maggio. Maggiori informazioni nella locandina allegata.

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Sussex probability seminar
by Enrico Scalas 19 Apr '21

19 Apr '21

Care colleghe e colleghi, vi invio l'annuncio del seminario di Vladislav Vysotskiy il 26 aprile a mezzogiorno. Le persone interessate possono ottenere il link contattando l'organizzatrice, Dr Minmin Wang (minmin.wang(a)sussex.ac.uk) Cordiali saluti, Enrico Scalas -- Next Monday (26th April) at 11am (UK time) there’ll be an online probability seminar given by Vladislav Vysotskiy. Title: How long is the convex minorant of a one-dimensional random walk? Abstract: We prove distributional limit theorems for the length of the largest convex minorant of a one dimensional random walk with independent identically distributed increments. Depending on the distribution of the increments there are several regimes with different limit distributions for the length. The most prominent of our results is a central limit theorem for the length in the case when the increments have zero mean and finite variance. Among other tools, we employ a representation of convex minorants of random walks in terms of uniform random permutations. This talk is based on a joint work with Gerold Alsmeyer, Zakhar Kabluchko, and Alexander Marynych.

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Corso SIMULATION AND INFERENCE IN POPULATION GENETICS
by Matteo Ruggiero 19 Apr '21

19 Apr '21

Cari colleghi, nell’ambito del programma di Visiting Professors della Laurea Magistrale in Stochastics and Data Science dell’Università di Torino (programma completo alla pagina https://www.master-sds.unito.it/go/visiting) con piacere annunciamo il seguente corso: -------------------------------------- Paul JENKINS (University of Warwick, UK) SIMULATION AND INFERENCE IN POPULATION GENETICS Population genetics provides a rich source of data. We now have the ability to sequence, cost-efficiently, the genomes of a large number of individuals from a species. Patterns of variation in DNA sequences offer a rich insight into biological and demographic processes: mutation, natural selection, past migration events, admixture, population structure, and so on. But such data are high-dimensional, noisy, and - because of shared ancestry - not independent, giving rise to some challenging statistical problems. In this course we will cover two important models for the analysis of genetic data - the coalescent, and the Wright-Fisher diffusion. We will discuss methods of simulation of data from these models, as well as how to perform inference for key biological and evolutionary parameters, using techniques such as MCMC. -------------------------------------- Il corso si svolgerà online secondo il seguente calendario - mar 27 Aprile, h.14-16 - mer 28 Aprile, h.16-18 - mar 4 Maggio, h.14-16 - mer 5 Maggio, h.16-18 - mer 12 Maggio, h.16-18 - mar 18 Maggio, h.14-16 - mer 19 Maggio, h.16-18 Il corso è rivolto agli studenti della Laurea Magistrale ma la partecipazione è aperta a tutti gli interessati, tramite le seguenti riunioni Webex valide rispettivamente per le lezioni del martedì e del mercoledì: https://unito.webex.com/unito/j.php?MTID=meeb9bd7865e8bc86b75074b346c0a3ed Ricorre ogni Martedì con validità 13/4/2021 fino a 18/5/2021 da 14:00 a 16:00 Numero riunione: 121 415 2525 Password: MEiAMZMf986 https://unito.webex.com/unito/j.php?MTID=m775c416c6142fd5b86bd7207f46dbabe Ricorre ogni Mercoledì con validità 14/4/2021 fino a 19/5/2021 da 16:00 a 18:00 Numero riunione: 121 469 7803 Password: C5RsPRapS92 Cordiali saluti, Matteo Ruggiero --- Matteo Ruggiero University of Torino and Collegio Carlo Alberto www.matteoruggiero.it

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Course ISI-ERS "An Introduction to Functional Data Analysis for Density Functions in Bayes spaces"
by Alessandra Menafoglio 19 Apr '21

19 Apr '21

We cordially invite you to the short course "An Introduction to Functional Data Analysis for Density Functions in Bayes spaces”, which will be held on 29-30 April 2021, both days from 14:00 alle 17:00 (GMT+2). The course is part of the initiatives of the International Statistical Institute (ISI-ERS). It aims to provide participants with an overview on the models and methods today available for the analysis of distributional data (e.g., probability densities) by using the geometry of Bayes spaces. Further information on the course is available at: https://iasc-isi.org/events/iasc-ers-course-an-introduction-to-functional-d… <https://iasc-isi.org/events/iasc-ers-course-an-introduction-to-functional-d…> Participation to the webinars is free of charge, but registration is requested using the link below: https://register.gotowebinar.com/register/8667082239416059148 <https://register.gotowebinar.com/register/8667082239416059148> Best regards, Alessandra Menafoglio Karel Hron Jitka Machalova **Abstract** The analysis of distributional data (probability density functions or histogram data) has recently gained increasing attention in the applications. Distributional data are often observed by themselves, or as result of aggregation of large streams of data. The course will provide an introduction to the analysis of these data using a Functional Data Analysis (FDA) approach, grounded on the perspective of Bayes spaces. These spaces are mathematical spaces whose points are densities (or, more generally, measures), which generalize to the FDA setting the Aitchison simplex for multivariate compositional data. The course will give an overview of the theory of Bayes spaces, as well as of statistical methods developed in this setting. All the methods will be illustrated through examples from real case studies. — Alessandra Menafoglio MOX - Dept. of Mathematics Politecnico di Milano Piazza Leonardo da Vinci, 32, 20133 Milan - Italy Phone: +39 02 2399 4642 Email: alessandra.menafoglio(a)polimi.it

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