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 201225 of 393 papers

TitleStatusHype
Hierarchical Agglomerative Graph Clustering in Nearly-Linear Time0
Vertex-Centric Visual Programming for Graph Neural Networks0
DIGRAC: Digraph Clustering Based on Flow ImbalanceCode0
Local Algorithms for Finding Densely Connected ClustersCode0
Local Algorithms for Estimating Effective Resistance0
_2-norm Flow Diffusion in Near-Linear Time0
A Comprehensive Survey on Community Detection with Deep Learning0
Seeing All From a Few: Nodes Selection Using Graph Pooling for Graph Clustering0
Seastar: vertex-centric programming for graph neural networks0
Query Driven-Graph Neural Networks for Community Search: From Non-Attributed, Attributed, to Interactive Attributed0
Multilayer Graph Clustering with Optimized Node Embedding0
Structure-Aware Face Clustering on a Large-Scale Graph with 10^7 NodesCode1
Learning a Proposal Classifier for Multiple Object TrackingCode1
Accurate Learning of Graph Representations with Graph Multiset PoolingCode1
Weighted Graph Nodes Clustering via Gumbel Softmax0
Effective and Scalable Clustering on Massive Attributed Graphs0
Refining a -nearest neighbor graph for a computationally efficient spectral clusteringCode0
Calibrating and Improving Graph Contrastive LearningCode0
Generative hypergraph clustering: from blockmodels to modularityCode1
Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNsCode1
Asymmetric Semi-Nonnegative Matrix Factorization for Directed Graph ClusteringCode0
Asymmetric Semi-Nonnegative Matrix Factorization for Directed Graph ClusteringCode0
Polaratio: A magnitude-contingent monotonic correlation metric and its improvements to scRNA-seq clusteringCode0
Semi-supervised Hyperspectral Image Classification with Graph Clustering Convolutional Networks0
Interpretable Clustering on Dynamic Graphs with Recurrent Graph Neural NetworksCode1
Show:102550
← PrevPage 9 of 16Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1R-DGAEACC70.5Unverified
2R-GMM-VGAEACC68.9Unverified
3AGCACC67Unverified
4RWR-GAEACC61.6Unverified
5RWR-VGAEACC61.3Unverified
6ARGEACC57.3Unverified
7ARVGEACC54.4Unverified
8GAEACC40.8Unverified
9DAEGC+GSCAN†NMI39.9Unverified
#ModelMetricClaimedVerifiedStatus
1R-GMM-VGAEACC76.7Unverified
2R-DGAEACC73.7Unverified
3AGCACC68.92Unverified
4RWR-VGAEACC68.5Unverified
5RWR-GAEACC66.9Unverified
6ARGEACC64Unverified
7ARVGEACC63.8Unverified
8GAEACC59.6Unverified
9DAEGC+GSCAN†NMI52.4Unverified
#ModelMetricClaimedVerifiedStatus
1R-GMM-VGAEACC74Unverified
2RWR-VGAEACC73.6Unverified
3RWR-GAEACC72.6Unverified
4R-DGAEACC71.4Unverified
5AGCACC69.78Unverified
6VGAEACC65.48Unverified
7DAEGC+GSCAN†NMI31.7Unverified
#ModelMetricClaimedVerifiedStatus
1Polaratio Consensus ClusteringAdjusted Rand Index1Unverified
#ModelMetricClaimedVerifiedStatus
1Polaratio Consensus ClusteringAdjusted Rand Index0.57Unverified
#ModelMetricClaimedVerifiedStatus
1Polaratio Consensus ClusteringAdjusted Rand Index0.46Unverified
#ModelMetricClaimedVerifiedStatus
1Polaratio Consensus ClusteringAdjusted Rand Index0.91Unverified
#ModelMetricClaimedVerifiedStatus
1Polaratio Consensus ClusteringAdjusted Rand Index0.95Unverified
#ModelMetricClaimedVerifiedStatus
1Polaratio Consensus ClusteringAdjusted Rand Index0.81Unverified
#ModelMetricClaimedVerifiedStatus
1Polaratio Consensus ClusteringAdjusted Rand Index0.81Unverified