方法证据记录
Multilayer Stochastic Block Model
The Multilayer Stochastic Block Model (ML-SBM) is a generative probabilistic framework that extends the classical stochastic block model to networks with multiple relation types or layers. It simultaneously infers community structure and block-to-block connection probabilities across all layers, capturing how communities cohere differently depending on context or relationship type.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Multilayer Stochastic Block Model (ML-SBM)
分类方法记录 · ml-model / network-analysis
- Peixoto, T. P. (2015). Inferring the mesoscale structure of layered, edge-valued, and time-varying networks. Physical Review E, 92(4), 042807. · DOI 10.1103/PhysRevE.92.042807
- De Bacco, C., Power, E. A., Larremore, D. B., & Moore, C. (2017). Community detection, link prediction, and layer interdependence in multilayer networks. Physical Review E, 95(4), 042317. · DOI 10.1103/PhysRevE.95.042317
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