317 citations · 864 across the 6 of their papers we have counts for
6 papers
Spectra of random networks with arbitrary degrees
M. E. J. Newman, Xiao Zhang, Raj Rao Nadakuditi
We derive a message passing method for computing the spectra of locally tree-like networks and an approximation to it that allows us to compute closed-form expressions or fast nume…
Random graph models for dynamic networks
Xiao Zhang, Cristopher Moore, M. E. J. Newman
We propose generalizations of a number of standard network models, including the classic random graph, the configuration model, and the stochastic block model, to the case of time-…
Multiway spectral community detection in networks
Xiao Zhang, M. E. J. Newman
One of the most widely used methods for community detection in networks is the maximization of the quality function known as modularity. Of the many maximization techniques that ha…
Identification of core-periphery structure in networks
Xiao Zhang, Travis Martin, M. E. J. Newman
Many networks can be usefully decomposed into a dense core plus an outlying, loosely-connected periphery. Here we propose an algorithm for performing such a decomposition on empiri…
Localization and centrality in networks
Travis Martin, Xiao Zhang, M. E. J. Newman
Eigenvector centrality is a common measure of the importance of nodes in a network. Here we show that under common conditions the eigenvector centrality displays a localization tra…
Spectra of random graphs with community structure and arbitrary degrees
Xiao Zhang, Raj Rao Nadakuditi, M. E. J. Newman
Using methods from random matrix theory researchers have recently calculated the full spectra of random networks with arbitrary degrees and with community structure. Both reveal in…