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10 01 24 IM random one dimensional NoticiaProbability Seminar “Inhomogeneous percolation with random one-dimensional reinforcements”

January 15, from 3:30 p.m. to 4:30 p.m. (Rio de Janeiro local time)

Local: room C116 - Bloco C - CT – Instituto de Matemática – UFRJ. There will be no transmission online.

Speaker: Alan Bruno do Nascimento (UFMG)

Abstract: In this talk we consider inhomogeneous Bernoulli bond percolation on the graph GxZ, where G is an infinite connected graph with bounded degree and Z is the set of integers. In 1994, Madras, Schinazi and Schonman showed that there is no percolation in Z^d  if the edges  are open with a probability of q<1 if they lie on a fixed axis and with a probability of p<p_c(Z^d) otherwise. Here, we consider a region given by boxes with iid radii centered along the vertical axis 0xZ of GxZ. We allow each edge to be open with a probability of q<1 if it is inside this region and with a probability of p<p_c(GxZ) otherwise. The goal of the talk is to show that, even if the region is connected, occurrence or not of percolation in this inhomogeneous model depends on how sparse and how large are the boxes placed along the axis. We aim to give sufficient conditions on the moments of the radii as a function of the growth of the graph G for percolation not to occur.
This is a joint work with Rémy Sanchis and Daniel Ungaretti.

More complete information about the seminars can be found at DME

Organizers: Giulio Iacobelli e Maria Eulalia Vares

IM wordcloud12 NoticiaProbability Seminar ''Causal Inference Under Mis-Specification: Adjustment Based on the Propensity Score''

December 11, from 3:30 p.m. to 4:30 p.m. (Rio de Janeiro local time)

Local: room C116 - Bloco C - CT – Instituto de Matemática – UFRJ

Speaker:  Widemberg da Silva Nobre (IM-UFRJ)

Abstract: We study Bayesian approaches to causal inference via propensity score regression. Much of Bayesian methodology relies on parametric and distributional assumptions, with presumed correct specification, whereas the extant propensity score methods in Bayesian literature have relied on approaches that cannot be viewed as fully Bayesian in the context of conventional ‘likelihood times prior’ posterior inference. We emphasize that causal inference is typically carried out in settings of mis-specification, and develop strategies for fully Bayesian inference that reflect this. We focus on methods based on decision-theoretic arguments, and show how inference based on loss-minimization can give valid and fully Bayesian inference. We propose a computational approach to inference based on the Bayesian bootstrap which has good Bayesian and frequentist properties.

Link of the paper HERE.

More complete information about the seminars can be found at DME.

Sincerely,

Organizers: Giulio Iacobelli e Maria Eulalia Vares

03 11 IM ProbabilitySeminar noticiaProbability Seminar "Stein’s method and asymptotic independence" November 6, from 3:30 p.m. to 4:30 p.m. (Rio de Janeiro local time)

Local: Google Meet

Speaker: Ciprian Tudor (Université de Lille)
Abstract: If Y is a random vector in R^d we denote by P_Y its probability distribution. Consider a random variable X and a d-dimensional random vector Y. We develop a multidimensional variant of the Stein-Malliavin calculus which allows to measure the Wasserstein distance between the law P_(X, Y) and the probability distribution P_Z x P_Y, where Z is a Gaussian random variable. That is, we give estimates, in terms of the Malliavin operators, for the distance between the law of the random vector  (X, Y) and the law of the vector (Z,Y), where Z is Gaussian and independent of Y.

Then we focus on the particular case of random vectors in Wiener chaos and we give an asymptotic version of this result. In this situation, this variant of the Stein-Malliavin calculus has strong and unexpected consequences.

More complete information about the seminars can be found at DME.

27 11 IM Seminário NoticiaProbability Seminar ''On a Dyson-fractional Brownian motion'' November 27, from 3:30 p.m. to 4:30 p.m. (Rio de Janeiro local time)

Local: Transmissão Online

Clique AQUI para acessar a transmissão.

Speaker: Victor Pérez-Abreu (Guanajuato, Mexico)

Abstract: This talk will present an overview of the behavior of the eigenvalues of the fractional Brownian matrix motion and other related matrix processes. We emphasize on a possible extension of the Dyson-Brownian motion, namely the dynamics of the eigenvalues processes and their non-colliding property, the limit of the associated empirical process, as well as the free Brownian motion and the non commutative fractional Brownian motion.

More complete information about the seminars can be found at DME.

Sincerely,

Organizers: Giulio Iacobelli e Maria Eulalia Vares

24 10 IM ProbabilitySeminar noticiaTitle: "Properties of the gradient squared of the Gaussian free field"
Speaker: Sergio I. López  (Universidad Nacional Autónoma de México)
Date: 30/10/2023
Time: 3:30 p.m. to 4:30 p.m. (Rio de Janeiro local time)
Local: Online

This meeting will take place on Google Meet, through the link HERE.

Abstract: In this talk we study the scaling limit of a random field which is a non-linear transformation of the gradient Gaussian free field. More precisely, our object of interest is the recentered square of the norm of the gradient Gaussian free field at every point of the square lattice. Surprisingly, in dimension 2 this field bears a very close connection to the height-one field of the Abelian sandpile model studied in Dürre (2009). In fact, with different methods we are able to obtain the same scaling limits of the height-one field: on the one hand, we show that the limiting cumulants are identical (up to a sign change) with the same conformally covariant property, and on the other that the same central limit theorem holds when we view the interface as a random distribution. We generalize these results to higher dimensions as well.

Joint work with Rajat Subhra Hazra (Leiden), Alan Rapoport (Utrecht) and Wioletta Ruszel (Utrecht)

More complete information about the seminars can be found at HERE

Sincerely,

Organizers: Giulio Iacobelli e Maria Eulalia Vares

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