方法证据记录
Bayesian Stochastic Block Model
The Bayesian Stochastic Block Model (Bayesian SBM) is a principled probabilistic method for community detection in networks. It treats group membership as a latent variable and uses Bayesian inference to simultaneously recover block structure and select the number of communities, avoiding the resolution-limit bias that plagues modularity-based approaches.
源记录
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Bayesian Stochastic Block Model (Bayesian SBM)
分类方法记录 · ml-model / network-analysis
- Peixoto, T. P. (2014). Efficient Monte Carlo and greedy heuristic for the inference of stochastic block models. Physical Review E, 89(1), 012804. · DOI 10.1103/PhysRevE.89.012804
- Nowicki, K., & Snijders, T. A. B. (2001). Estimation and prediction for stochastic blockstructures. Journal of the American Statistical Association, 96(455), 1077–1087. · DOI 10.1198/016214501753208735
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