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Community Detection

Community Detection is one of the fundamental problems in network analysis, where the goal is to find groups of nodes that are, in some sense, more similar to each other than to the other nodes.

Source: Randomized Spectral Clustering in Large-Scale Stochastic Block Models

Papers

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Showing 151–200 of 919 papers

TitleStatusHype
An Effective Index for Truss-based Community Search on Large Directed Graphs—0
Community Detection in the Multi-View Stochastic Block Model—0
Fundamental limits of community detection from multi-view data: multi-layer, dynamic and partially labeled block models—0
Mixture of multilayer stochastic block models for multiview clustering—0
Learning Persistent Community Structures in Dynamic Networks via Topological Data AnalysisCode0
Systematic review of image segmentation using complex networks—0
A Community Detection and Graph Neural Network Based Link Prediction Approach for Scientific Literature—0
Benchmarking Evolutionary Community Detection Algorithms in Dynamic Networks—0
A Framework for Exploring Federated Community Detection—0
Uncertainty in GNN Learning Evaluations: A Comparison Between Measures for Quantifying Randomness in GNN Community Detection—0
Uncovering communities of pipelines in the task-fMRI analytical space—0
A Structural-Clustering Based Active Learning for Graph Neural NetworksCode0
Community Detection in High-Dimensional Graph Ensembles—0
Almost Exact Recovery in Gossip Opinion Dynamics over Stochastic Block Models—0
Localizing and Assessing Node Significance in Default Mode Network using Sub-Community Detection in Mild Cognitive Impairment—0
Understanding Opinions Towards Climate Change on Social Media—0
Self-similarity of Communities of the ABCD Model—0
Single-cell Multi-view Clustering via Community Detection with Unknown Number of ClustersCode0
Optimal Clustering of Discrete Mixtures: Binomial, Poisson, Block Models, and Multi-layer Networks—0
Revealing Cortical Layers In Histological Brain Images With Self-Supervised Graph Convolutional Networks Applied To Cell-Graphs—0
Narratives from GPT-derived Networks of News, and a link to Financial Markets Dislocations—0
Unsupervised Graph Attention Autoencoder for Attributed Networks using K-means Loss—0
Community-Aware Efficient Graph Contrastive Learning via Personalized Self-Training—0
Unsupervised segmentation of irradiationx2010induced orderx2010disorder phase transitions in electron microscopyCode0
Structure and inference in hypergraphs with node attributesCode0
Choose A Table: Tensor Dirichlet Process Multinomial Mixture Model with Graphs for Passenger Trajectory ClusteringCode0
Generalized Category Discovery with Clustering Assignment Consistency—0
Community Detection Guarantees Using Embeddings Learned by Node2Vec—0
Explaining Interactions Between Text SpansCode0
Analyzing Modularity Maximization in Approximation, Heuristic, and Graph Neural Network Algorithms for Community Detection—0
Spoofing Attack Detection in the Physical Layer with Robustness to User Movement—0
Restricted Tweedie Stochastic Block Models—0
Evading Community Detection via Counterfactual Neighborhood Search—0
The Map Equation Goes Neural: Mapping Network Flows with Graph Neural NetworksCode0
Matrix Factorization in Tropical and Mixed Tropical-Linear Algebras—0
Topology-Agnostic Detection of Temporal Money Laundering Flows in Billion-Scale Transactions—0
A Comprehensive Review of Community Detection in Graphs—0
Using network metrics to explore the community structure that underlies movement patterns—0
GroupEnc: encoder with group loss for global structure preservation—0
Consistency of Lloyd's Algorithm Under Perturbations—0
A stochastic block model for community detection in attributed networks—0
Computational Lower Bounds for Graphon Estimation via Low-degree Polynomials—0
Superpixels algorithms through network community detectionCode0
LSCPM: communities in massive real-world Link Streams by Clique Percolation MethodCode0
Optimal Noise Reduction in Dense Mixed-Membership Stochastic Block Models under Diverging Spiked Eigenvalues Condition—0
Optimizing parameter search for community detection in time evolving networks of complex systems—0
Curvature-based Clustering on Graphs—0
A Neural Collapse Perspective on Feature Evolution in Graph Neural NetworksCode0
Normalized mutual information is a biased measure for classification and community detectionCode0
Privacy-Preserving Community Detection for Locally Distributed Multiple Networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GNNAccuracy-NE2—Unverified
2CommunityGANF1-score0.09—Unverified
3Ego-SplittingF1-score0.04—Unverified
#ModelMetricClaimedVerifiedStatus
1EdMotNMI0.42—Unverified
2CDNMFNMI0.4—Unverified
#ModelMetricClaimedVerifiedStatus
1CDNMFACC0.48—Unverified
#ModelMetricClaimedVerifiedStatus
1CommunityGANF1-Score0.15—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.56—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.69—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.65—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.68—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.71—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.57—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.86—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.85—Unverified
#ModelMetricClaimedVerifiedStatus
1CDNMFACC0.67—Unverified