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 2650 of 919 papers

TitleStatusHype
LouvainNE: Hierarchical Louvain Method for High Quality and Scalable Network EmbeddingCode1
MultiVERSE: a multiplex and multiplex-heterogeneous network embedding approachCode1
New Frontiers in Graph Autoencoders: Joint Community Detection and Link PredictionCode1
Random Walk on Multiple NetworksCode1
Correlation-based feature selection to identify functional dynamics in proteinsCode1
Amortized Probabilistic Detection of Communities in GraphsCode1
A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research ChallengesCode1
Boosting Multitask Learning on Graphs through Higher-Order Task AffinitiesCode1
A network approach to topic modelsCode1
Breaking the Batch Barrier (B3) of Contrastive Learning via Smart Batch MiningCode1
Adversarial Attack on Community Detection by Hiding IndividualsCode1
Community detection using fast low-cardinality semidefinite programmingCode1
ConGraT: Self-Supervised Contrastive Pretraining for Joint Graph and Text EmbeddingsCode1
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on GraphsCode1
Artificial Benchmark for Community Detection (ABCD): Fast Random Graph Model with Community StructureCode1
Explainable Global Wildfire Prediction Models using Graph Neural NetworksCode1
Extended Stochastic Block Models with Application to Criminal NetworksCode1
Fast Sequence-Based Embedding with Diffusion GraphsCode1
Community Detection in Bipartite Networks with Stochastic BlockmodelsCode1
Deep Learning for Community Detection: Progress, Challenges and OpportunitiesCode1
GeoAI-Enhanced Community Detection on Spatial Networks with Graph Deep LearningCode1
Hierarchical Message-Passing Graph Neural NetworksCode1
Hypergraph Contrastive Learning for Drug Trafficking Community DetectionCode1
IncNSA: Detecting communities incrementally from time-evolving networks based on node similarityCode1
Self-Supervised Learning of Object Parts for Semantic SegmentationCode1
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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