Hybrid maximum likelihood inference for stochastic block models
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Publication:2129593
DOI10.1016/j.csda.2022.107449OpenAlexW4210981077WikidataQ114191866 ScholiaQ114191866MaRDI QIDQ2129593
Maria Francesca Marino, Silvia Pandolfi
Publication date: 22 April 2022
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2022.107449
Uses Software
Cites Work
- Variational Inference for Stochastic Block Models From Sampled Data
- Asymptotic normality of maximum likelihood and its variational approximation for stochastic blockmodels
- Detecting communities and their evolutions in dynamic social networks -- a Bayesian approach
- Estimating the dimension of a model
- Bootstrap methods: another look at the jackknife
- Estimation and prediction for stochastic blockmodels for graphs with latent block structure
- Dealing with reciprocity in dynamic stochastic block models
- Consistency of maximum-likelihood and variational estimators in the stochastic block model
- Improved Bayesian inference for the stochastic block model with application to large networks
- Model-based clustering of large networks
- A classification EM algorithm for clustering and two stochastic versions
- A note on pseudolikelihood constructed from marginal densities
- Estimation and Prediction for Stochastic Blockstructures
- New Consistent and Asymptotically Normal Parameter Estimates for Random-Graph Mixture Models
- Accuracy of variational estimates for random graph mixture models
- Model selection and clustering in stochastic block models based on the exact integrated complete data likelihood
- Variational Bayesian inference and complexity control for stochastic block models
- Statistical Clustering of Temporal Networks Through a Dynamic Stochastic Block Model
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