mlsanityData to 14 Oct 2026

A Review of Stochastic Block Models and Extensions for Graph Clustering

arXiv 1903.00114 ↗First posted 1 Mar 2019stat.ML cs.LGcited by 46

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Abstract (arXiv)

There have been rapid developments in model-based clustering of graphs, also known as block modelling, over the last ten years or so. We review different approaches and extensions proposed for different aspects in this area, such as the type of the graph, the clustering approach, the inference approach, and whether the number of groups is selected or estimated. We also review models that combine block modelling with topic modelling and/or longitudinal modelling, regarding how these models deal with multiple types of data. How different approaches cope with various issues will be summarised and compared, to facilitate the demand of practitioners for a concise overview of the current status of these areas of literature.

Key facts. Cited by 46 papers in the map (data through 14 Oct 2026). First posted on arXiv 1 Mar 2019.

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Citing papers per year: 2021: 6; 2022: 5; 2023: 9; 2024: 13; 2025: 8; 2026: 5.

46 papers.

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  1. 2021A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learningcited by 55
  2. 2022Synthetic Graph Generation to Benchmark Graph Learningcited by 16
  3. 2024Advancing Graph Generation through Beta Diffusioncited by 13
  4. 2023A Comprehensive Review of Community Detection in Graphscited by 12
  5. 2021Partition and Code: learning how to compress graphscited by 10
  6. 2022Using Embeddings for Causal Estimation of Peer Influence in Social Networkscited by 9
  7. 2024Learning on Large Graphs using Intersecting Communitiescited by 8
  8. 2023The effect of network topologies on fully decentralized learning: a preliminary investigationcited by 7
  9. 2024Impact of network topology on the performance of Decentralized Federated Learningcited by 7
  10. 2024Supra-Laplacian Encoding for Transformer on Dynamic Graphscited by 6
  11. 2022Sparse Subspace Clustering in Diverse Multiplex Network Modelcited by 4
  12. 2023A Comprehensive Survey on Graph Summarization with Graph Neural Networkscited by 4
34 more
  1. 2024Differentially private exact recovery for stochastic block modelscited by 4
  2. 2023Symmetrical SyncMap for Imbalanced General Chunking Problemscited by 3
  3. 2021Semi-Supervised Clustering with Inaccurate Pairwise Annotationscited by 2
  4. 2021Alignment and Comparison of Directed Networks via Transition Couplings of Random Walkscited by 2
  5. 2023Restricted Tweedie Stochastic Block Modelscited by 2
  6. 2024Large Generative Graph Modelscited by 2
  7. 2022flow-based clustering and spectral clustering: a comparisoncited by 1
  8. 2023Containing a spread through sequential learning: to exploit or to explore?cited by 1
  9. 2024Inference and Visualization of Community Structure in Attributed Hypergraphs Using Mixed-Membership Stochastic Block Modelscited by 1
  10. 2024Advanced Graph Clustering Methods: A Comprehensive and In-Depth Analysiscited by 1
  11. 2024Estimating the number of clusters of a Block Markov Chaincited by 1
  12. 2024A Dirichlet stochastic block model for composition-weighted networkscited by 1
  13. 2024PieClam: A Universal Graph Autoencoder Based on Overlapping Inclusive and Exclusive Communitiescited by 1
  14. 2025Deep Graph Learning will stall without Network Sciencecited by 1
  15. 2025Are GNNs doomed by the topology of their input graph?cited by 1
  16. 2025Relational Database Distillation: From Structured Tables to Condensed Graph Datacited by 1
  17. 2021Statistical embedding: Beyond principal componentscited by 0
  18. 2021Identifying bias in cluster quality metricscited by 0
  19. 2022Recurrent segmentation meets block models in temporal networkscited by 0
  20. 2023Dynamic Mixed Membership Stochastic Block Model for Weighted Labeled Networkscited by 0
  21. 2023A Simple Quantum Blockmodeling with Qubits and Permutationscited by 0
  22. 2023Auto-encoding GPS data to reveal individual and collective behaviourcited by 0
  23. 2024Network-based Neighborhood regressioncited by 0
  24. 2024Hierarchical Blockmodelling for Knowledge Graphscited by 0
  25. 2025Urban delineation through the lens of commute networks: Leveraging graph embeddings to distinguish socioeconomic groups in citiescited by 0
  26. 2025Model-free algorithms for fast node clustering in SBM type graphs and application to social role inference in animalscited by 0
  27. 2025Node Classification via Simplicial Interaction with Augmented Maximal Clique Selectioncited by 0
  28. 2025Rethinking Graph Super-resolution: Dual Frameworks for Topological Fidelitycited by 0
  29. 2025Learning Multi-Order Block Structure in Higher-Order Networkscited by 0
  30. 2026Matching and mixing: Matchability of graphs under Markovian errorcited by 0
  31. 2026Bridging Maximum Likelihood and Optimal Transport for Efficient Inference and Model Selection in Stochastic Block Modelscited by 0
  32. 2026Schreier-Coset Graph Rewiringcited by 0
  33. 2026Fuzzy network jump models for soft dynamic clustering of graph-structured datacited by 0
  34. 2026T-ARC: Topology-Aware Randomized Clustering via Distributionally Robust Stochastic Block Modelscited by 0