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 151175 of 393 papers

TitleStatusHype
RuDSI: graph-based word sense induction dataset for RussianCode1
Approximate sampling and estimation of partition functions using neural networksCode0
Rethinking Symmetric Matrix Factorization: A More General and Better Clustering PerspectiveCode0
Stochastic Parallelizable Eigengap Dilation for Large Graph Clustering0
flow-based clustering and spectral clustering: a comparison0
NCAGC: A Neighborhood Contrast Framework for Attributed Graph ClusteringCode1
Conversation Group Detection With Spatio-Temporal Context0
Align then Fusion: Generalized Large-scale Multi-view Clustering with Anchor Matching CorrespondencesCode1
Hippocluster: an efficient, hippocampus-inspired algorithm for graph clusteringCode0
Simple Contrastive Graph Clustering0
Deep Graph Clustering via Mutual Information Maximization and Mixture Model0
Reducing Neural Architecture Search Spaces with Training-Free Statistics and Computational Graph Clustering0
SCGC : Self-Supervised Contrastive Graph ClusteringCode1
Simulate Time-integrated Coarse-grained Molecular Dynamics with Multi-Scale Graph NetworksCode1
Attributed Graph Clustering with Dual Redundancy ReductionCode1
CGC: Contrastive Graph Clustering for Community Detection and TrackingCode0
Model Reduction of Consensus Network Systems via Selection of Optimal Edge Weights and Nodal Time-Scales0
SMARAGD: Learning SMatch for Accurate and Rapid Approximate Graph DistanceCode0
Spectral Graph Clustering for Intentional Islanding Operations in Resilient Hybrid Energy Systems0
Graph clustering with Boltzmann machines0
Skew-Symmetric Adjacency Matrices for Clustering Directed Graphs0
A Dynamic Mode Decomposition Approach for Decentralized Spectral Clustering of Graphs0
Improved Dual Correlation Reduction Network0
Recovering Unbalanced Communities in the Stochastic Block Model With Application to Clustering with a Faulty Oracle0
Efficient graph convolution for joint node representation learning and clusteringCode1
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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