A Review of Stochastic Block Models and Extensions for Graph Clustering

1 March 2019

Papers citing "A Review of Stochastic Block Models and Extensions for Graph Clustering"

11 / 11 papers shown

Title
PieClam: A Universal Graph Autoencoder Based on Overlapping Inclusive and Exclusive Communities Daniel Zilberg Ron Levie 31 0 0 18 Sep 2024
Differentially private exact recovery for stochastic block models Dung Nguyen Anil Vullikanti 36 2 0 04 Jun 2024
Impact of network topology on the performance of Decentralized Federated Learning Luigi Palmieri C. Boldrini Lorenzo Valerio A. Passarella M. Conti 34 5 0 28 Feb 2024
Inference and Visualization of Community Structure in Attributed Hypergraphs Using Mixed-Membership Stochastic Block Models Kazuki Nakajima Takeaki Uno 48 1 0 01 Jan 2024
Symmetrical SyncMap for Imbalanced General Chunking Problems Heng Zhang Danilo Vasconcellos Vargas 11 0 0 16 Oct 2023
Semiparametric Modeling and Analysis for Longitudinal Network Data Yinqiu He Jiajin Sun Yuang Tian Z. Ying Yang Feng 25 1 0 23 Aug 2023
The effect of network topologies on fully decentralized learning: a preliminary investigation Luigi Palmieri Lorenzo Valerio C. Boldrini A. Passarella 16 8 0 29 Jul 2023
A Bayesian Nonparametric Stochastic Block Model for Directed Acyclic Graphs Clement D Lee Marco Battiston 19 0 0 18 Jan 2023
Extended Stochastic Block Models with Application to Criminal Networks Sirio Legramanti T. Rigon Daniele Durante David B. Dunson 30 20 0 16 Jul 2020
Scalable MCMC for Mixed Membership Stochastic Blockmodels Wenzhe Li Sungjin Ahn Max Welling BDL 32 42 0 16 Oct 2015
Parsimonious module inference in large networks Tiago P. Peixoto MoE 45 200 0 19 Dec 2012