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by Laura Maria Morato 13 Nov '23

13 Nov '23

cari tutti il mio indirizzo email e' cambiato. Il nuovo e' morato.lauramaria(a)gmail.com

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Seminar in Statistics - SVEN WANG
by Pierpaolo De Blasi 13 Nov '23

13 Nov '23

SEMINARS IN STATISTICS @ COLLEGIO CARLO ALBERTO <https://www.carloalberto.org/events/category/seminars/seminars-in-statistic…> Venerdi 17 Novembre 2023, alle ore 12.00, presso il Collegio Carlo Alberto, in Piazza Arbarello 8, Torino, si terrà il seguente seminario: ------------------------------------------------ Speaker: Sven Wang (Humboldt University Berlin, Germany) Title: *Statistical convergence rates for transport- and ODE-based generative models* Abstract: Measure transport provides a powerful toolbox for estimation and generative modelling of complicated probability distributions. The common principle is to learn a transport map which couples a tractable (e.g. uniform or normal) reference distribution to some complicated target distribution, e.g. by maximizing a likelihood objective. In this talk, we discuss recent advances in statistical convergence guarantees for such methods. While a general theory is developed, we will primarily treat (1) triangular maps which are the building blocks for ’autoregressive normalizing flows’ and (2) ODE-based maps, defined through an ODE flow. The latter encompasses NeuralODEs, a popular method for generative modeling. Our results imply that transport methods achieve minimax-optimal convergence rates for non-parametric density estimation over Hölder classes on the unit cube. Based on the papers arXiv:2207.10231 and arXiv:2309.01043, joint with Youssef Marzouk (MIT, United States), Robert Ren (MIT, United States) and Jakob Zech (U Heidelberg, Germany). ------------------------------------------------ Sarà possibile seguire il seminario anche in streaming: Join Zoom Meeting <https://us02web.zoom.us/j/84606225203?pwd=aFhFa2RKaWtVd2V6R2Rpc05hRGNodz09> Il seminario è organizzato dalla "de Castro" Statistics Initiative www.carloalberto.org/stats -- Pierpaolo De Blasi University of Torino & Collegio Carlo Alberto carloalberto.org/pdeblasi <https://sites.google.com/a/carloalberto.org/pdeblasi/>

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[owps] One world probability seminar on Thursday 16 November
by Ilya Chevyrev 13 Nov '23

13 Nov '23

Dear all. The next session of the One World Probability Seminar will be next week on Thursday (November 16) from 14:00 to 16:00 UTC time. The speakers of this session are Elisabetta Candellero (Universita Roma Tre) and Thomas Finn (Durham University). Title, abstract and the zoom link are below the signature and can be also found on the website https://www.owprobability.org/one-world-probability-seminar. Kind regards, Ilya Chevyrev and Julio Backhoff. Title: Coexistence in competing first-passage percolation Abstract: Consider the following random competition model on a given graph G that is driven by two first-passage percolation processes FPP_1 and FPP_\lambda. Initially, FPP_1 occupies a single site and FPP_\lambda is dormant in seeds that are placed on the sites of G as a product of Bernoulli measures of parameter p. Then, FPP_1 spreads through the edges of G at rate 1 and FPP_\lambda spreads from seeds at rate \lambda when that seed is attempted to be occupied by either FPP_1 or FPP_\lambda. Once a site is occupied by either process it remains occupied by that process henceforth. This model is known as first-passage percolation in a hostile environment (FPPHE) and was first introduced by Sidoravicius and Stauffer ’19. In the first talk, we establish that FPPHE is non-monotone in the sense that increasing p or \lambda may increase the probability that FPP_1 occupies infinitely many sites through constructing a quasi-transitive graph where such behaviour holds. The non-monotonicity of FPPHE makes understanding the phase transitions of the model extremely challenging. We prove that a regime of coexistence exists on hyperbolic and non-amenable vertex transitive graphs where both FPP_1 and FPP_\lambda concurrently occupy infinite connected components with positive probability. In the second talk, we prove that a regime of coexistence also holds on Z^d for d>2 through the introduction of a refined multi-scale analysis that can handle non-equilibrium and non-monotone processes. We relate this proof to recent work on multi-particle diffusion limited aggregation by Sidoravicius and Stauffer ’19 and the SIR model by Dauvergne and Sly ’22 where FPPHE is a crucial analytical tool in understanding non-equilibrium particle systems. Based on joint work with Alexandre Stauffer. Speaker 1 (14:00-15:00 UTC): Elisabetta Candellero (Universita Roma Tre). Speaker 2 (15:00-16:00 UTC): Thomas Finn (Durham University). Zoom-link: https://univienna.zoom.us/j/69711117344?pwd=Y3cwMEI3VkZKSTh5RVZRSGhRN3lUdz09 Meeting ID: 697 1111 7344 Passcode: 305805

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seminario di eugenio regazzini a bologna
by Pietro Rigo 12 Nov '23

12 Nov '23

Giovedi' 16 novembre 2023, alle ore 16, nell'aula III del dipartimento di scienze statistiche di Bologna, Eugenio Regazzini terra' un seminario dal titolo: On the number of elements beyond the ones effectively observed Oltre che in presenza, e' possibile assistere al seminario collegandosi alla piattaforma Microsoft Teams: Fai clic qui per partecipare alla riunione<https://teams.microsoft.com/l/meetup-join/19%3ameeting_ZGRhYmVhZjAtYWFiZS00…>

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EFI9 - Call for Papers (fwd)
by Tiziano Vargiolu 11 Nov '23

11 Nov '23

Apologies for cross-posting --------------------------------------------------------------------------- Second Call for Papers: Energy Finance Italia 9 Conference (EFI9) University of Bari, February 12-14, 2024 Deadline for submission of organized sessions: November 27, 2023 Deadline for extended abstracts/papers: December 4, 2023 Web: https://events.math.unipd.it/EFI9 Contact: efi9(a)uniba.it The Conference puts together researchers and practitioners working in all areas of Energy-Finance & Climate-Change related research in economics, finance, engineering, data science and mathematics. Participants are encouraged to submit their papers or proposals of organized sessions on a wide range of theoretical and applied topics in these two research fields, such as (but not limited to): Energy and climate data science, Energy forecasting, Energy innovations, Energy markets, Energy analytics, Energy mix and carbon emission trading, Energy supply chain, ESG, Green finance & financing energy infrastructure, Climate policy and risk, Climate change & market efficiency, Climate change & pricing uncertainty, Regulation and regulatory risk, Renewable sources, Risk measurement and management, Storage devices, Sustainable finance. Keynote speaker: Ruediger Kiesel Award: Best EFI9 Paper, reserved to the presenters born after January 1st, 1994 Special issue of Energy Economics associated with this conference We are looking forward to welcoming you in Bari. for the organizing committee Viviana Fanelli and Tiziano Vargiolu

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6-year university assistant position in Probability in Vienna
by Prof. Fabio Toninelli 10 Nov '23

10 Nov '23

Dear friends and colleagues, the Technical University of Vienna is advertising a *6-year university assistant (postdoc) position in probability theory, *within the Mathematical Stochastics research group (https://www.tuwien.at/en/mg/mstoch) <https://www.tuwien.at/en/mg/mstoch>*/ <https://www.tuwien.at/en/mg/mstoch> /* Deadline for applications: *January 4th, 2024*. Starting date: *October 2024* For the official announcement, the link to the application portal and details on the position, see here: https://jobs.tuwien.ac.at/Job/220480 Please forward this to potentially interested candidates Best wishes Fabio Toninelli and Marcin Lis -- Prof. Dr. Fabio Toninelli Technical University of Vienna Institut für Stochastik und Wirtschaftsmathematik Wiedner Hauptstrasse 8-10, 1040 Wien, Austria Office: 6th floor, green area. tel: +43-1-58801-10570 https://sites.google.com/view/fabio-toninelli/home

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Post-doctoral position at the University of Torino
by Matteo Ruggiero 09 Nov '23

09 Nov '23

2-year post-doctoral position at the University of Torino DESCRIPTION Project title: Statistical inference for continuous-state hidden Markov models Project supervisor: Matteo Ruggiero - www.matteoruggiero.it The project will focus on the development of statistical methodologies and computational strategies for signal retrieval and parameter inference in the setting of continuous-state hidden Markov models, with envisioned applications in Bayesian inference and population dynamics. The research activity can be adapted to the profile and interests of the successful candidate regarding both the specific topic and the research approach. The successful candidate will also be part of the research group at the "de Castro" Statistics Initiative (https://www.carloalberto.org/stats), based at Collegio Carlo Alberto. FURTHER DETAILS - Gross salary: EUR 40,000 per year. Travel funds will also be made available. - Planned starting date: Jan 1st, 2024 (with some flexibility on postponement) - Contract: 24 months, subject to positive evaluation of the research activity after the first year. - Requirements: * Degree: already holding a PhD title is preferential but not mandatory. * Required background: solid knowledge of stochastic processes and provable coding skills. * Preferential background: familiarity with hidden Markov models and/or Bayesian inference and/or stochastic population dynamics. - Link to call: https://webapps.unito.it/albo_ateneo/ (Numero di repertorio: 5412) - Link to apply: https://pica.cineca.it/unito/ - Deadline: November 23rd, 2023. Further enquiries can be directed at matteo.ruggiero(a)unito.it. Best regards, Matteo Ruggiero --- Matteo Ruggiero University of Torino and Collegio Carlo Alberto www.matteoruggiero.it

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Post-doc position - Sapienza University of Rome (Dep. Statistical Sciences)
by Luisa Beghin 08 Nov '23

08 Nov '23

Dear All, a call for *one-year** post-doc position* (renewable up to further 12 months) is open at the *Department of Statistical Sciences, Sapienza University in Rome.* The topic of the research is “Anomalous diffusions: non-Gaussian Analysis and grey noises". The details of the call are at https://web.uniroma1.it/trasparenza/dettaglio_bando 23_AR-B_MAT/06 <https://web.uniroma1.it/trasparenza/dettaglio_bando_albo/210254> The position is open to graduates who do not yet hold a Ph.D. Salary: €19,367 (gross). The *deadline is 4 december 2023*. For technical assistance on application please contact domenica.zumpano(a)uniroma1.it I would be grateful if you could forward this message to any potentially interested candidate. Thanks and best regards, Luisa Beghin *************************************************************** Luisa Beghin Dipartimento di Scienze Statistiche Fac. Ingegneria dell'Informazione, Informatica e Statistica "SAPIENZA" Università di Roma Piazzale Aldo Moro 5, 00185 Roma T (+39) 06 49910543 F (+39) 06 4959241 https://sites.google.com/site/luisabeghin/ ***************************************************************** -- **Fai crescere le giovani ricercatrici e i giovani ricercatori* **con il 5 per mille alla Sapienza *Scrivi il codice fiscale dell'Università *80209930587 Cinque per mille <https://www.uniroma1.it/it/node/23149>*

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22 novembre ore 16.00 - Seminario Prof. Simone Vantini
by Enea Bongiorno 08 Nov '23

08 Nov '23

Carissimi colleghi, scusandomi per eventuali invii multipli, vi inoltro il seguente annuncio di seminario. Tutti gli interessati sono invitati a partecipare. Cordialmente, Enea Bongiorno -------------------------------- 22 novembre ore 16.00 - aula 206, campus Perrone, via Perrone, 18, Novara. Università del Piemonte Orientale. - on-line: https://meet.google.com/ign-wqer-sjs *Finite-sample exact prediction bands for functional data* *Prof. Simone Vantini, Politecnico di Milano* *Abstract:* The talk will deal with the key challenge of creating prediction bands for a new observation in the functional data framework given a training set of observed functional data and possibly in presence of covariates, either scalar, categorical, or functional. Starting from the investigation of the literature concerning this topic, we propose an innovative approach building on top of Conformal Prediction and Functional Data Analysis able to overcome the main drawbacks associated to the existing approaches. Under minimal distributional assumptions (i.e., exchangeability of the random functions), we will show how the new proposed nonparametric method (i) is able to provide prediction regions which could visualized in the form of bands, (ii) is guaranteed with exact coverage probability also for finite sample sizes, and finally (iii) is computational efficient. Different specifications of the method will be compared in terms of efficiency in some simulated and real case scenarios also in the case of multi-dimensional domain and/or codomain. ----------------------------------- Locandina dell'evento <https://drive.google.com/drive/folders/1VJXOiNVwkDI8w2wE0hMqcjFgVzEa7vi4?us…> Seminari Matematici Statistici <https://sites.google.com/uniupo.it/seminari-ms/home-page> ----------------------------------- -- Enea Bongiorno,PhD Associate Professor of Statistics Università degli Studi del Piemonte Orientale Via Perrone 18, 28100, Novara, Italia Phone: +390321375317 enea.bongiorno(a)uniupo.it upobook.uniupo.it/enea.bongiorno

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Hooke Research Fellowships at the University of Oxford (fwd)
by Tiziano Vargiolu 07 Nov '23

07 Nov '23

---------- Forwarded message ---------- Date: Tue, 7 Nov 2023 15:42:20 +0000 (GMT) From: Rama Cont <Rama.Cont(a)maths.ox.ac.uk> To: vargiolu(a)math.unipd.it Subject: Hooke Research Fellowships at the University of Oxford Hooke Postdoctoral Research Fellowships Mathematical & Computational Finance Group Mathematical Institute, University of Oxford https://www.maths.ox.ac.uk/node/65978 Deadline: 22 November 2023 The Oxford Mathematical & Computational Finance Group invite applications from talented researchers with interests in Stochastic analysis, Mathematical Finance or Data Science for a Hooke Research Fellowship starting September 2024. These prestigious Fellowships at the University of Oxford are full-time, fixed term up to 36 months starting September 2024 and provide an ideal opportunity for candidates to pursue an independent research programme. Successful applicants will be free to conduct their own research programme. To aid the development of their academic profile, Fellows will be required to contribute up to three hours of departmental teaching per week for the 24 weeks of each academic year, averaged over the period of the Fellowship to allow for extended visits elsewhere. Candidates will have, or be close to completing, a PhD in mathematics or a related discipline. They must show evidence of independence and the ability to undertake research of the highest academic standard, hold an outstanding record of papers published in major international journals (commensurate with career stage), and have a relevant research plan which would enhance the Mathematical Institute’s research profile. Additional information about the post, and a full list of selection criteria, are available here: https://www.maths.ox.ac.uk/node/65978 Please direct informal enquiries to recruitment(a)maths.ox.ac.uk, quoting vacancy reference 168995. Applicants should read the job description before writing their application. You will be required to upload a supporting letter setting out how you meet the selection criteria, a curriculum vitae including full list of publications with top three papers starred, a statement of research interests including a plan for research during the Fellowship, and the names and contact details of two referees as part of your online application. NOTE: Applicants are responsible for contacting their referees and making sure that their letters are received by the closing date. Applications for this vacancy are to be made online. To apply for this post and for further details, including a job description and selection criteria, please click on the link below: https://my.corehr.com/pls/uoxrecruit/erq_jobspec_details_form.jobspec?p_id= 168995 Only applications received before 12:00 noon UK time on 22 November 2023 can be considered. Oxford is committed to equality and valuing diversity. CLOSING DATE: 22 NOVEMBER 2023 - 12:00 UK TIME

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