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SUMMARY:Properties of Latent Variable Network Models - Nial Friel (Univers
 ity College Dublin)
DTSTART:20160715T103000Z
DTEND:20160715T110000Z
UID:TALK66773@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:We derive properties of Latent Variable Models for networks\, 
 a broad class of models that includes the widely-used Latent Position Mode
 ls. We characterise several features of interest\, with particular focus o
 n the degree distribution\, clustering coefficient\, average path length a
 nd degree correlations. We introduce the Gaussian Latent Position Model\, 
 and derive analytic expressions and asymptotic approximations for its netw
 ork properties. We pay particular attention to one special case\, the Gaus
 sian Latent Position Model with Random Effects\, and show that it can repr
 esent heavy-tailed degree distributions\, positive asymptotic clustering c
 oefficients and small-world behaviour that often occur in observed social 
 networks. Finally\, we illustrate the ability of the models to capture imp
 ortant features of real networks through several well known datasets.
LOCATION:Seminar Room 1\, Newton Institute
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