Weighted stochastic block model
type: Item
instance of: scholarly article
title: Weighted stochastic block model
zbMATH Open document ID: 1477.62153
author: Tin Lok James Ng
author: Thomas Brendan Murphy
published in: Statistical Methods and Applications
publication date: 2022-01-14T00:00:00Z
Mathematics Subject Classification ID: 62H22
Mathematics Subject Classification ID: 62F12
Mathematics Subject Classification ID: 62H30
Mathematics Subject Classification ID: 05C80
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 7457585
zbMATH Keywords: weighted stochastic block model
zbMATH Keywords: variational estimators
zbMATH Keywords: maximum likelihood estimators
zbMATH Keywords: consistency
zbMATH Keywords: model selection
MaRDI profile type: Publication
full work available at URL: s10260-021-00590-6
OpenAlex ID: W3199189318
cites work: Community Detection and Stochastic Block Models
cites work: Mixed membership stochastic blockmodels
cites work: Learning latent block structure in weighted networks
cites work: Identifiability of parameters in latent structure models with many observed variables
cites work: Parameter identifiability in a class of random graph mixture models
cites work: New Consistent and Asymptotically Normal Parameter Estimates for Random-Graph Mixture Models
cites work: A Bernstein-type inequality for suprema of random processes with applications to model selection in non-Gaussian regression
cites work: A nonparametric view of network models and Newman–Girvan and other modularities
cites work: The method of moments and degree distributions for network models
cites work: Asymptotic normality of maximum likelihood and its variational approximation for stochastic blockmodels
cites work: Consistency and asymptotic normality of latent block model estimators
cites work: Consistency of maximum-likelihood and variational estimators in the stochastic block model
cites work: Classification and estimation in the stochastic blockmodel based on the empirical degrees
cites work: Stochastic blockmodels with a growing number of classes
cites work: Model selection and clustering in stochastic block models based on the exact integrated complete data likelihood
cites work: Overlapping stochastic block models with application to the French political blogosphere
cites work: Model selection in overlapping stochastic block models
cites work: Detection of structurally homogeneous subsets in graphs
cites work: Inference for a generalised stochastic block model with unknown number of blocks and non-conjugate edge models
cites work: Uncovering latent structure in valued graphs: a variational approach
cites work: Bayesian degree-corrected stochastic blockmodels for community detection
cites work: Computing Communities in Large Networks Using Random Walks
cites work: Spectral clustering and the high-dimensional stochastic blockmodel
cites work: Estimation and prediction for stochastic blockmodels for graphs with latent block structure
cites work: Likelihood-based model selection for stochastic block models
cites work: Closed-Form Estimators for the Gamma Distribution Derived From Likelihood Equations
cites work: Strategies for online inference of model-based clustering in large and growing networks
DOI: 10.1007/S10260-021-00590-6
description: scientific article; zbMATH DE number 7457585