The stochastic topic block model for the clustering of vertices in networks with textual edges

Model selection and clustering in stochastic block models based on the exact integrated complete data likelihood

(2015) Etienne Côme et al.   STATISTICAL MODELLING

The random subgraph model for the analysis of an ecclesiastical network in Merovingian Gaul

(2014) Yacine Jernite et al.   Annals of Applied Statistics

Probabilistic topic models

(2012) David M. Blei   COMMUNICATIONS OF THE ACM

Improved Bayesian inference for the stochastic block model with application to large networks

(2012) Aaron F. McDaid et al.   COMPUTATIONAL STATISTICS & DATA ANALYSIS

Variational Bayesian inference and complexity control for stochastic block models

(2012) P Latouche et al.   STATISTICAL MODELLING

Review of statistical network analysis: models, algorithms, and software

(2012) M. Salter-Townshend et al.   Statistical Analysis and Data Mining

Overlapping stochastic block models with application to the French political blogosphere

(2011) Pierre Latouche et al.   Annals of Applied Statistics

Uncovering latent structure in valued graphs: A variational approach

(2010) Mahendra Mariadassou et al.   Annals of Applied Statistics

Detecting communities and their evolutions in dynamic social networks—a Bayesian approach

(2010) Tianbao Yang et al.   MACHINE LEARNING

Clustering based on random graph model embedding vertex features

(2010) Hugo Zanghi et al.   PATTERN RECOGNITION LETTERS

A mixture of experts latent position cluster model for social network data

(2010) Isobel Claire Gormley et al.   Statistical Methodology

A nonparametric view of network models and Newman–Girvan and other modularities

(2009) Peter J. Bickel et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Fast unfolding of communities in large networks

(2008) Vincent D Blondel et al.   JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT

Fast online graph clustering via Erdős–Rényi mixture

(2008) Hugo Zanghi et al.   PATTERN RECOGNITION

Bayesian Approach to Network Modularity

(2008) Jake M. Hofman et al.   PHYSICAL REVIEW LETTERS