skip to content
 

Inference and large-scale structure in networks

Presented by: 
Mark Newman University of Michigan
Date: 
Thursday 15th September 2016 - 14:00 to 15:00
Venue: 
INI Seminar Room 2
Abstract: 
Characterization of network structure as focused on two different scales: small-scale structure, represented by properties such as degrees, correlations, and clustering, and large-scale structure, which is most commonly presented in terms of modules and community detection.  This talk will focus on large-scale structure, but with the aim of getting away from community structure, which is well-trodden ground, and looking at other forms.  Working with generative models and a range of model-based inference techniques, I'll talk about overlapping communities, hierarchical structure, latent-space structure, ranking, and core-periphery structure, among others.
The video for this talk should appear here if JavaScript is enabled.
If it doesn't, something may have gone wrong with our embedded player.
We'll get it fixed as soon as possible.
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons