SOTAVerified

Graph Clustering

Graph Clustering is the process of grouping the nodes of the graph into clusters, taking into account the edge structure of the graph in such a way that there are several edges within each cluster and very few between clusters. Graph Clustering intends to partition the nodes in the graph into disjoint groups.

Source: Clustering for Graph Datasets via Gumbel Softmax

Papers

Showing 351–375 of 393 papers

TitleStatusHype
Learning-based Efficient Graph Similarity Computation via Multi-Scale Convolutional Set MatchingCode0
Random projection tree similarity metric for SpectralNetCode0
Real-time Trajectory-based Social Group DetectionCode0
Learning Networks from Random Walk-Based Node SimilaritiesCode0
Learning Persistent Community Structures in Dynamic Networks via Topological Data AnalysisCode0
Learning Resolution Parameters for Graph ClusteringCode0
SMARAGD: Learning SMatch for Accurate and Rapid Approximate Graph DistanceCode0
The Map Equation Goes Neural: Mapping Network Flows with Graph Neural NetworksCode0
Local Algorithms for Finding Densely Connected ClustersCode0
Local Clustering for Lung Cancer Image Classification via Sparse Solution TechniqueCode0
Balancing the Tradeoff Between Clustering Value and InterpretabilityCode0
Refining a k-nearest neighbor graph for a computationally efficient spectral clusteringCode0
Refining a -nearest neighbor graph for a computationally efficient spectral clusteringCode0
GraphLearner: Graph Node Clustering with Fully Learnable AugmentationCode0
Balanced Multi-Relational Graph ClusteringCode0
Reliable Node Similarity Matrix Guided Contrastive Graph ClusteringCode0
A Versatile Framework for Attributed Network Clustering via K-Nearest Neighbor AugmentationCode0
Comparison and Benchmark of Graph Clustering AlgorithmsCode0
Residual Gated Graph ConvNetsCode0
Adaptive Local Clustering over Attributed GraphsCode0
Attributed Graph Clustering via Adaptive Graph ConvolutionCode0
Rethinking Symmetric Matrix Factorization: A More General and Better Clustering PerspectiveCode0
Spectral Clustering for Directed Graphs via Likelihood Estimation on Stochastic Block ModelsCode0
MeanCut: A Greedy-Optimized Graph Clustering via Path-based Similarity and Degree Descent CriterionCode0
Attributed Graph Clustering: A Deep Attentional Embedding ApproachCode0
Show:102550
← PrevPage 15 of 16Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1R-DGAEACC70.5—Unverified
2R-GMM-VGAEACC68.9—Unverified
3AGCACC67—Unverified
4RWR-GAEACC61.6—Unverified
5RWR-VGAEACC61.3—Unverified
6ARGEACC57.3—Unverified
7ARVGEACC54.4—Unverified
8GAEACC40.8—Unverified
9DAEGC+GSCAN†NMI39.9—Unverified
#ModelMetricClaimedVerifiedStatus
1R-GMM-VGAEACC76.7—Unverified
2R-DGAEACC73.7—Unverified
3AGCACC68.92—Unverified
4RWR-VGAEACC68.5—Unverified
5RWR-GAEACC66.9—Unverified
6ARGEACC64—Unverified
7ARVGEACC63.8—Unverified
8GAEACC59.6—Unverified
9DAEGC+GSCAN†NMI52.4—Unverified
#ModelMetricClaimedVerifiedStatus
1R-GMM-VGAEACC74—Unverified
2RWR-VGAEACC73.6—Unverified
3RWR-GAEACC72.6—Unverified
4R-DGAEACC71.4—Unverified
5AGCACC69.78—Unverified
6VGAEACC65.48—Unverified
7DAEGC+GSCAN†NMI31.7—Unverified
#ModelMetricClaimedVerifiedStatus
1Polaratio Consensus ClusteringAdjusted Rand Index1—Unverified
#ModelMetricClaimedVerifiedStatus
1Polaratio Consensus ClusteringAdjusted Rand Index0.57—Unverified
#ModelMetricClaimedVerifiedStatus
1Polaratio Consensus ClusteringAdjusted Rand Index0.46—Unverified
#ModelMetricClaimedVerifiedStatus
1Polaratio Consensus ClusteringAdjusted Rand Index0.91—Unverified
#ModelMetricClaimedVerifiedStatus
1Polaratio Consensus ClusteringAdjusted Rand Index0.95—Unverified
#ModelMetricClaimedVerifiedStatus
1Polaratio Consensus ClusteringAdjusted Rand Index0.81—Unverified
#ModelMetricClaimedVerifiedStatus
1Polaratio Consensus ClusteringAdjusted Rand Index0.81—Unverified