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

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Showing 176–200 of 919 papers

TitleStatusHype
Community Detection by Principal Components Clustering Methods—0
Community detection by spectral methods in multi-layer networks—0
Community Detection: Exact Recovery in Weighted Graphs—0
Community Detection Clustering via Gumbel Softmax—0
Community Detection for Heterogeneous Multiple Social Networks—0
Community Detection for Power Systems Network Aggregation Considering Renewable Variability—0
Community Detection from Multiple Observations: from Product Graph Model to Brain Applications—0
Community Detection Graph Convolutional Network for Overlap-Aware Speaker Diarization—0
A new method for quantifying network cyclic structure to improve community detection—0
Community detection in censored hypergraph—0
Community detection in complex networks via node similarity, graph representation learning, and hierarchical clustering—0
Community Detection in Cryptocurrencies with Potential Applications to Portfolio Diversification—0
Community Detection in Degree-Corrected Block Models—0
Community Detection in General Hypergraph via Graph Embedding—0
A Spectral Framework for Anomalous Subgraph Detection—0
Community Detection in High-Dimensional Graph Ensembles—0
Community Detection in Medical Image Datasets: Using Wavelets and Spectral Methods—0
Community Detection in Multi-frequency EEG Networks—0
Community detection in multiplex networks using locally adaptive random walks—0
Community detection in multiplex networks based on orthogonal nonnegative matrix tri-factorization—0
Community detection in multi-relational data with restricted multi-layer stochastic blockmodel—0
Community detection in network neuroscience—0
A Multi-Strategy Approach to Overcoming Bias in Community Detection Evaluation—0
Community detection in networks: Structural communities versus ground truth—0
Achieving the KS threshold in the general stochastic block model with linearized acyclic belief propagation—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