[FRIAM] Fwd: Seminar Announcement- Statistical Neuroscience Seminar

[Tom Johnson]

Too bad we're not in Boston.

---------- Forwarded message ---------
From: Daniel Lewis Sussman <sussman at bu.edu>
Date: Wed, Jan 22, 2020, 11:25 PM
Subject: Fwd: Seminar Announcement- Statistical Neuroscience Seminar
To: <prob-sem at math.bu.edu>, <stat-seminar at math.bu.edu>


In case you haven't already received this, please see below for the
announcement for this week's Probability and Statistics seminar.

---------- Forwarded message ---------

Hi All,



The Department of Mathematics & Statistics are happy to present the
Statistical Neuroscience Seminar with our guest speaker *Keith Levin on
January 23rd, 4pm in MCS B39*. Please see below for the full seminar
announcement.



*Statistical Neuroscience Seminar*



*Keith Levin*

Bootstrapping Networks with Latent Geometric Structure

January 23rd, 4pm MCS B39

Tea and Cookies at 3:30pm



A core problem in statistical network analysis is to develop network
analogues of classical statistical techniques. The problem of bootstrapping
network data stands out as especially challenging, owing to the dependency
structure of network data and the fact that one typically observes only a
single network, rather than a sample. In this talk, I will present a method
for generating bootstrap samples for networks drawn from latent space
models, a class of network models in which unobserved geometric structure
drives network topology. We show consistency of the proposed bootstrap
method under the random dot product graph, a latent space model that
includes the popular stochastic blockmodel as a special case, though the
method is applicable to any latent space model in which the latent geometry
can be recovered suitably accurately. In the second half of the talk, I
will outline a few ongoing projects applying this bootstrap method and
several related network analysis techniques to neuroscientific data
obtained from fMRI studies. Common to these projects is the presence of
latent low-dimensional network structure that we wish to relate to
patient-level covariates such as age or disease status.





*Kimberly Capri *

Staff Coordinator

Department of Mathematics & Statistics

Boston University

kmcapri at bu.edu

P: (617) 353-2560
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