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

Showing 201225 of 919 papers

TitleStatusHype
A Structural-Clustering Based Active Learning for Graph Neural NetworksCode0
Modularity Based Community Detection in HypergraphsCode0
Community detection in networks without observing edgesCode0
MPI-FAUN: An MPI-Based Framework for Alternating-Updating Nonnegative Matrix FactorizationCode0
Constraint-Induced Symmetric Nonnegative Matrix Factorization for Accurate Community DetectionCode0
A Deep Latent Space Model for Graph Representation LearningCode0
Non-Convex Exact Community Recovery in Stochastic Block ModelCode0
Normalized mutual information is a biased measure for classification and community detectionCode0
On Graph Neural Networks versus Graph-Augmented MLPsCode0
Community detection in sparse time-evolving graphs with a dynamical Bethe-HessianCode0
Online Tensor Methods for Learning Latent Variable ModelsCode0
On semidefinite relaxations for the block modelCode0
Overlapping community detection in networks based on link partitioning and partitioning around medoidsCode0
Community Detection in the Stochastic Block Model by Mixed Integer ProgrammingCode0
Constrained fractional set programs and their application in local clustering and community detectionCode0
Community Detection in Weighted Multilayer Networks with Ambient NoiseCode0
Block-Structure Based Time-Series Models For Graph SequencesCode0
Perfect Spectral Clustering with Discrete CovariatesCode0
Community detection over a heterogeneous population of non-aligned networksCode0
CommunityGAN: Community Detection with Generative Adversarial NetsCode0
Community detection using diffusion informationCode0
Community Detection with Graph Neural NetworksCode0
Community detection with spiking neural networks for neuromorphic hardwareCode0
PRUNE: Preserving Proximity and Global Ranking for Network EmbeddingCode0
CHIP: A Hawkes Process Model for Continuous-time Networks with Scalable and Consistent EstimationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GNNAccuracy-NE2Unverified
2CommunityGANF1-score0.09Unverified
3Ego-SplittingF1-score0.04Unverified
#ModelMetricClaimedVerifiedStatus
1EdMotNMI0.42Unverified
2CDNMFNMI0.4Unverified
#ModelMetricClaimedVerifiedStatus
1CDNMFACC0.48Unverified
#ModelMetricClaimedVerifiedStatus
1CommunityGANF1-Score0.15Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.56Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.69Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.65Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.68Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.71Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.57Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.86Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.85Unverified
#ModelMetricClaimedVerifiedStatus
1CDNMFACC0.67Unverified