Weighted stochastic block model (Q2066716)

scientific article; zbMATH DE number 7457585

Language	Label	Description	Also known as
English	Weighted stochastic block model	scientific article; zbMATH DE number 7457585

Statements

instance of

scholarly article

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title

Weighted stochastic block model (English)

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author

Tin Lok James Ng

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Thomas Brendan Murphy

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published in

Statistical Methods and Applications

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publication date

14 January 2022

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zbMATH Keywords

weighted stochastic block model

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variational estimators

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maximum likelihood estimators

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consistency

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model selection

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MaRDI profile type

Publication

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full work available at URL

https://doi.org/10.1007/s10260-021-00590-6

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cites work

Community Detection and Stochastic Block Models

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Mixed membership stochastic blockmodels

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Learning latent block structure in weighted networks

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Identifiability of parameters in latent structure models with many observed variables

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Parameter identifiability in a class of random graph mixture models

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New Consistent and Asymptotically Normal Parameter Estimates for Random-Graph Mixture Models

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A Bernstein-type inequality for suprema of random processes with applications to model selection in non-Gaussian regression

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

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The method of moments and degree distributions for network models

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Asymptotic normality of maximum likelihood and its variational approximation for stochastic blockmodels

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Consistency and asymptotic normality of latent block model estimators

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Consistency of maximum-likelihood and variational estimators in the stochastic block model

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Classification and estimation in the stochastic blockmodel based on the empirical degrees

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Stochastic blockmodels with a growing number of classes

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

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Overlapping stochastic block models with application to the French political blogosphere

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Model selection in overlapping stochastic block models

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Detection of structurally homogeneous subsets in graphs

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Inference for a generalised stochastic block model with unknown number of blocks and non-conjugate edge models

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Uncovering latent structure in valued graphs: a variational approach

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Bayesian degree-corrected stochastic blockmodels for community detection

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Computing Communities in Large Networks Using Random Walks

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Spectral clustering and the high-dimensional stochastic blockmodel

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Estimation and prediction for stochastic blockmodels for graphs with latent block structure

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Likelihood-based model selection for stochastic block models

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Closed-Form Estimators for the Gamma Distribution Derived From Likelihood Equations

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Strategies for online inference of model-based clustering in large and growing networks

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Identifiers

zbMATH Open document ID

1477.62153

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Mathematics Subject Classification ID

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10.1007/S10260-021-00590-6

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Sitelinks

Mathematics(1 entry)

mardi Publication:2066716