SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 76–100 of 919 papers

TitleStatusHype
Introducing the modularity graph: an application to brain functional networks—0
Community Detection from Multiple Observations: from Product Graph Model to Brain Applications—0
Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning PerspectiveCode1
Network-community analysis of cellular senescence—0
Faithful Density-Peaks Clustering via Matrix Computations on MPI Parallelization SystemCode0
Community Detection in Networks: A Rough Sets and Consensus Clustering Approach—0
Bias-Corrected Joint Spectral Embedding for Multilayer Networks with Invariant Subspace: Entrywise Eigenvector Perturbation and Inference—0
Differentially private exact recovery for stochastic block models—0
Using RL to Identify Divisive Perspectives Improves LLMs Abilities to Identify Communities on Social Media—0
Signal-Plus-Noise Decomposition of Nonlinear Spiked Random Matrix Models—0
Regularized Projection Matrix Approximation with Applications to Community Detection—0
Simultaneous Identification of Sparse Structures and Communities in Heterogeneous Graphical Models—0
LGDE: Local Graph-based Dictionary ExpansionCode0
Community Detection for Heterogeneous Multiple Social Networks—0
Robustness of graph embedding methods for community detectionCode0
Graph Vertex Embeddings: Distance, Regularization and Community Detection—0
Estimating mixed memberships in multi-layer networks—0
Bioregionalization analyses with the bioregion R-package—0
Graph-Based Optimisation of Network Expansion in a Dockless Bike Sharing System—0
Community detection by spectral methods in multi-layer networks—0
Node Centrality Approximation For Large Networks Based On Inductive Graph Neural Networks—0
VEC-SBM: Optimal Community Detection with Vectorial Edges CovariatesCode0
Learning dynamic representations of the functional connectome in neurobiological networksCode0
Analysis of Persian News Agencies on Instagram, A Words Co-occurrence Graph-based Approach—0
Explainable Global Wildfire Prediction Models using Graph Neural NetworksCode1
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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