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Stochastic block model

The stochastic block model is a generative model for random graphs. This model tends to produce graphs containing communities, subsets characterized… 
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Related topics

Related topics

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Belief propagationErdős–Rényi modelGenerative modelGraph (discrete mathematics)

Broader (1)

Machine learning

Papers overview

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2020
2020
Exact Recovery and Sharp Thresholds of Stochastic Ising Block Model
The stochastic block model (SBM) is a random graph model in which the edges are generated according to the underlying cluster… 
2019
2019
Efficient Distributed Community Detection in the Stochastic Block Model
Designing effective algorithms for community detection is an important and challenging problem in large-scale graphs, studied… 
2019
2019
Gaussian Mixture Models for Stochastic Block Models with Non-Vanishing Noise
Community detection tasks have received a lot of attention across statistics, machine learning, and information theory with work… 
2018
2018
Use-Relationship Based Classification for Software Components
In recent years, the maintenance period of the software system is increasing. The size of the software system has grown, and the… 
2018
2018
Recovery, detection and confidence sets of communities in a sparse stochastic block model
Posterior distributions for community assignment in the planted bi-section model are shown to achieve frequentist exact recovery… 
2017
2017
Exact integrated completed likelihood maximisation in a stochastic block transition model for dynamic networks
The latent stochastic block model is a flexible statistical model which is widely used for the analysis of network data… 
2016
2016
A Tractable Fully Bayesian Method for the Stochastic Block Model
The stochastic block model (SBM) is a generative model revealing macroscopic structures in graphs. Bayesian methods are used for… 
2015
2015
Optimal Bayesian estimation in stochastic block models
With the advent of structured data in the form of social networks, genetic circuits and protein interaction networks, statistical… 
2014
2014
Non-Reconstructability in the Stochastic Block Model
We consider the problem of clustering (or reconstruction) in the stochastic block model, in the regime where the average degree… 
2010
2010
Bayesian block modelling for weighted networks
This paper presents a Bayesian approach to block modelling weighted networks to identify role assignments. This data arises… 
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