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 101–150 of 393 papers

TitleStatusHype
CONVERT:Contrastive Graph Clustering with Reliable AugmentationCode1
Reinforcement Graph Clustering with Unknown Cluster NumberCode1
Homophily-enhanced Structure Learning for Graph ClusteringCode1
Examining the Effects of Degree Distribution and Homophily in Graph Learning ModelsCode1
Unpaired Multi-View Graph Clustering with Cross-View Structure MatchingCode0
Transforming Graphs for Enhanced Attribute Clustering: An Innovative Graph Transformer-Based Method—0
Multi-class Graph Clustering via Approximated Effective p-ResistanceCode0
G^2uardFL: Safeguarding Federated Learning Against Backdoor Attacks through Attributed Client Graph Clustering—0
arXiv4TGC: Large-Scale Datasets for Temporal Graph ClusteringCode0
Faster Approximation Algorithms for Parameterized Graph Clustering and Edge LabelingCode0
Dink-Net: Neural Clustering on Large GraphsCode2
Progressive Sub-Graph Clustering Algorithm for Semi-Supervised Domain Adaptation Speaker Verification—0
Multi-factor Sequential Re-ranking with Perception-Aware Diversification—0
Transfer operators on graphs: Spectral clustering and beyond—0
Deep Temporal Graph ClusteringCode1
Two to Five Truths in Non-Negative Matrix Factorization—0
Contrastive Graph Clustering in Curvature Spaces—0
Joint Graph Learning and Model Fitting in Laplacian Regularized Stratified ModelsCode0
Taming graph kernels with random featuresCode0
Human Semantic Segmentation using Millimeter-Wave Radar Sparse Point Clouds—0
Real-time Trajectory-based Social Group DetectionCode0
Feudal Graph Reinforcement LearningCode0
Spectral Toolkit of Algorithms for Graphs: Technical Report (1)Code1
Neural-prior stochastic block model—0
A parameter-free graph reduction for spectral clustering and SpectralNetCode0
Random projection tree similarity metric for SpectralNetCode0
Supervised Hierarchical Clustering using Graph Neural Networks for Speaker DiarizationCode0
Refining a k-nearest neighbor graph for a computationally efficient spectral clusteringCode0
Approximate spectral clustering with eigenvector selection and self-tuned kCode0
Approximate spectral clustering density-based similarity for noisy datasetsCode0
Simultaneous Linear Multi-view Attributed Graph Representation Learning and ClusteringCode1
ClusterFuG: Clustering Fully connected Graphs by MulticutCode0
Utilizing Technical Data to Discover Similar Companies in Dhaka Stock Exchange—0
Cluster-guided Contrastive Graph Clustering NetworkCode1
Sample-Level Multi-View Graph Clustering—0
Correlation Clustering Algorithm for Dynamic Complete Signed Graphs: An Index-based ApproachCode0
On Learning the Structure of Clusters in Graphs—0
Constant Approximation for Normalized Modularity and Associations Clustering—0
Influence-Based Mini-Batching for Graph Neural Networks—0
Hard Sample Aware Network for Contrastive Deep Graph ClusteringCode2
Learning a Fast 3D Spectral Approach to Object Segmentation and Tracking over Space and Time—0
GraphLearner: Graph Node Clustering with Fully Learnable AugmentationCode0
Dual Information Enhanced Multi-view Attributed Graph Clustering—0
A Survey of Deep Graph Clustering: Taxonomy, Challenge, Application, and Open ResourceCode1
Scalable and Effective Conductance-based Graph Clustering—0
EGRC-Net: Embedding-induced Graph Refinement Clustering NetworkCode0
Learning Optimal Graph Filters for Clustering of Attributed Graphs—0
Graph Fuzzy System: Concepts, Models and AlgorithmsCode0
Variational Graph Generator for Multi-View Graph ClusteringCode1
Efficient block contrastive learning via parameter-free meta-node approximationCode0
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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