Dear colleagues,
We are delighted to announce that the One World Probability Seminar is returning for the Spring 2025 semester with a refreshed schedule! The seminar will be held every other Wednesday at 14:00 UTC.
The season will kick off on Wednesday, March 12 at 14:00 UTC via Zoom (link<https://polimi-it.zoom.us/j/92945513591?pwd=zjtRwpHoO9kRyQuPPj4o186jXrvg1v.1>). We are thrilled to welcome our first two speakers:
Shankar Bhamidi (University of North Carolina) and David J. Aldous (UC Berkeley)
Please find titles and abstracts of their talks below and on our website<https://www.owprobability.org/about>, which also contains future speakers for the semester.
Originally launched during the early days of the pandemic to keep the probability community connected, our seminar has since hosted over 100 research talks from around the globe. It remains open to anyone eager to learn about the latest developments in probability theory. We encourage you to share this announcement as we embark on this new chapter.
If you want updates on future OWP seminars, consider joining our mailing list: here<https://www.owprobability.org/mailing-list> the instructions.
We look forward to seeing many of you online!
Best wishes,
Luisa Andreis and Roger Van Peski
Aldous’s fringe convergence of random trees and its applications
Shankar Bhamidi (UNC Chapel Hill)
Local weak convergence starting with the work of Aldous and Benjamini and Schramm has turned out to be one of the standard work horses in modern probabilistic combinatorics, to understand asymptotics of large discrete random structures and dynamics of processes such as random walks on such processes. The goal of this talk is to describe the impact of one of the less well known “OG” (original great) papers in this area: Aldous’s work on fringe convergence of random trees developed in a paper in the mid 90s. This technique, coupled with stochastic approximation techniques allows one to relatively easily prove local weak convergence of a number of modern random tree models proposed by domain scientists, including network evolution with limited choice, network dynamics where new individuals have access to only a partial temporal snapshot of the network and network evolution models where individuals have different attributes.
Obscure results and open problems: some of my favorites
David J. Aldous (UC Berkeley)
These are some problems that I would like some smart young person to work on!
(1) What probability distributions on $[0,\infty)$ arise as the distance between two i.i.d. points in some complete separable metric space?
(2) Probability distributions on routed planar networks.
(3) Combinatorics of fringe trees in a phylogenetic model.
(4) Nearest neighbor of nearest neighbor, on the complete network -- Are you smarter than an AI?
(5) Find a qualitatively realistic model for a generic subway network.
(6) Percolation of empires.
We are pleased to inform you that registration and fee payment are now
possible for the next Applied Bayesian Statistics summer school - ABS25
to be held from 3 to 6 June 2025 in the beautiful historic city of
Genova, overlooking the Ligurian Sea in Italy.
Website: https://abs25.imati.cnr.it/ <https://abs25.imati.cnr.it/>
The school is organized by CNR IMATI (Institute of Applied Mathematics
and Information Technologies at the Italian National Research Council in
Milano), in cooperation with the Department of Mathematics of the
University of Genova.
The topic will be SPATIO-TEMPORAL METHODS IN ENVIRONMENTAL EPIDEMIOLOGY
The lecturer will be Prof. ALEXANDRA SCHMIDT (McGill University,
Department of Epidemiology, Biostatistics and Occupational Health,
Canada), with the support of Dr. CARLO ZACCARDI (University G.
d'Annunzio Chieti-Pescara, Department of Economics, Italy).
As in the past (since 2004), there will be a combination of theoretical
and practical sessions, along with presentations by participants about
their work (past, current and future) related to the topic of the school.
OUTLINE: This course aims to explore the interface between environmental
epidemiology (EE) and spatio-temporal modelling (ST). The aim of EE is
to understand the adverse health effects of environmental hazards and to
estimate the risks associated with those hazards. Such risks have
traditionally been assessed either over time at a fixed point in space
or over space at a fixed point in time. ST modelling characterizes the
distribution of those hazards and associated risks over both
geographical locations and time. Understanding variation and exploiting
dependencies over both space and time greatly increases the power to
assess those relationships.
The course will cover a wide range of topics from an introduction to
spatio-temporal and epidemiological principles along with the
foundations of ST modeling, with specific focus on their application, to
new directions for research.
Topics to be covered:
- Types of epidemiological studies: cohort, case–control, ecological
- Measures of risk: relative risks, odds ratios, absolute risk,
sources of bias, assessing uncertainty
- Bayesian statistics and computational techniques: Markov Chain
Monte Carlo (MCMC)
- Regression models in epidemiology: Logistic and Poisson generalized
linear models, hierarchical models
- Dynamic linear models, temporal autocorrelation
- Spatial models: area and point referenced methods, mapping,
geostatistical methods, spatial regression
- Spatial-temporal models: separable models, non-separable models,
modelling exposures in space and time.
Reference:
Shaddick, G., Zidek, J.V., & Schmidt, A.M. (2023). Spatio–Temporal
Methods in Environmental Epidemiology with R (2nd ed.). Chapman and
Hall/CRC. https://doi.org/10.1201/9781003352655
<https://doi.org/10.1201/9781003352655>
We hope you will be interested in the school, and we would like to meet
you in Genova.
We invite you also to share the information with people potentially
interested.
Best regards
Elisa Varini and Fabrizio Ruggeri
Executive Director and Director of ABS25
Buongiorno, ricordiamo che *oggi lunedì 3 marzo dalle 16:30 alle 17:45* si
terrà il seminario on-line del gruppo UMI - PRISMA (
http://www.umi-prisma.polito.it/). I seminari PRISMA hanno un formato di
"colloquium" per creare un'occasione di scambio e discussione con tutta la
comunità dei probabilisti e statistici italiani. Ogni giornata comprende
due relatori che tengono due seminari di 30 minuti strettamente connessi,
per presentare alla comunità una prospettiva sul proprio ambito di ricerca.
Le registrazioni dei seminari vengono pubblicate sul canale YouTube
dell'UMI:
https://youtube.com/playlist?list=PLmySpc-jrtAMq84VH71evyqPc1hl6eEQb
I relatori di oggi saranno *Giuseppe Cannizzaro* (University of
Warwick) e *Fabio
Toninelli* (Technical University of Vienna) che parleranno di:
Teorema del Limite Centrale superdiffusivo per l'equazione di Burgers
stocastica alla dimensione critica.
con il seguente orario:
16:30 Primo seminario
17:00 Pausa e discussione
17:15 Secondo seminario
17:45 Conclusione e discussione
Trovate di seguito il riassunto. I seminari verranno trasmessi via Zoom al
seguente link:
https://unipd.zoom.us/j/81175434050?pwd=hCozT8gqnlu49Io6LawZWAwLDrnaJ7.1
Meeting ID: 811 7543 4050
Passcode: 871716
Vi aspettiamo numerosi!
Alberto Chiarini e Sonia Mazzucchi
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RELATORI: Giuseppe Cannizzaro (University of Warwick) e Fabio Toninelli
(Technical University of Vienna)
TITOLO: Teorema del Limite Centrale superdiffusivo per l'equazione di
Burgers stocastica alla dimensione critica
RIASSUNTO: L'equazione di Burgers Stocastica (EBS) è stata introdotta da
van Beijren, Kutner and Spohn per modellizzare sistemi diffusivi
asimmetrici con una singola quantità conservata (e.g. il modello di
esclusione semplice asimmetrico). Nella dimensione sub-critica d=1, EBS
coincide con la derivata dell'equazione KPZ il cui comportamento a grandi
scale è superdiffusivo con crescita polinomiale e le cui fluttuazioni
coincidono con il KPZ Fixed Point, mentre nelle dimensioni super-critiche
d>2, è diffusivo e converge a un'equazione del calore stocastica
anisotropica. Alla dimensione critica, è stato congetturato che la EBS sia
superdiffusiva con crescita logaritmica con un esponente preciso ma ciò è
stato mostrato solo modulo correzioni di ordine inferiore. Il presente
seminario è basato su un lavoro assieme a Quentin Moulard
https://arxiv.org/abs/2501.00344, in cui indentifichiamo la
superdiffusività e deriviamo le asintotiche della matrice di diffusione in
modo esatto. Inoltre, dimostriamo che nel limite di scala corretto, ovvero
che tiene presente della crescita logaritmiche alla diffusività, la
soluzione di EBS soddisfa un teorema del limite centrale. Il nostro è il
primo limite di scala superdiffusivo per un'equazione alle derivate
parziali stocastica critica, al di là dell'ambito di applicabilità della
teoria delle strutture di regolarità di Hairer.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Buongiorno a tutti,
Vorremmo segnalarvi che venerdì prossimo (7 Marzo) in aula 2BC30 (Torre Archimede, Università di Padova) ci sarà un seminario per il ciclo di seminari in Probabilità e Finanza di:
Marc Hoffman (Université Paris-Dauphine)
<https://www.ceremade.dauphine.fr/~hoffmann/> https://www.ceremade.dauphine.fr/~hoffmann/
Title: Some questions in mathematical statistics linked to evolution PDEs
Date: March 7, 2025, at 14:30, room 2BC30
Abstract: Evolution models in applications are often analysed via PDEs, interpreted as a macroscopic decription of the phenomenon of interest. This classical approach is nevertheless challenged by empirical data for model validation, especially when the phenomenon of interest does not depend on well established physical laws. In particular the statistical inference of parameters (estimation and testing) requires a underlying stochastic model. This is usullay treated via some addition of noise, sometimes artificially and always a bit arbitrarily. Relying on some specific examples that appear in population biology (cell growth, human demography) or agent-based models in economy, we propose an alternative approach. Starting from a microscopic stochastic model that can be partially observed and for which the PDE of interest is a mean-field limit, the intrinsic statistical noise becomes the fluctuation between the empirical measure of the particle system and the solution of the PDE. We will outline a rigorous statistical program in this setting and will give some results on McKean-Vlasov models that shall emphasise the interest of our approach.
Vi aspettiamo numerosi!
Alberto Chiarini e Alekos Cecchin
Sito web del seminario: https://www.math.unipd.it/~chiarini/seminars/