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 151–200 of 393 papers

TitleStatusHype
Efficient block contrastive learning via parameter-free meta-node approximationCode0
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 Clustering—0
flow-based clustering and spectral clustering: a comparison—0
NCAGC: A Neighborhood Contrast Framework for Attributed Graph ClusteringCode1
Conversation Group Detection With Spatio-Temporal Context—0
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 Clustering—0
Deep Graph Clustering via Mutual Information Maximization and Mixture Model—0
Reducing Neural Architecture Search Spaces with Training-Free Statistics and Computational Graph Clustering—0
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-Scales—0
SMARAGD: Learning SMatch for Accurate and Rapid Approximate Graph DistanceCode0
Spectral Graph Clustering for Intentional Islanding Operations in Resilient Hybrid Energy Systems—0
Graph clustering with Boltzmann machines—0
Skew-Symmetric Adjacency Matrices for Clustering Directed Graphs—0
A Dynamic Mode Decomposition Approach for Decentralized Spectral Clustering of Graphs—0
Improved Dual Correlation Reduction Network—0
Recovering Unbalanced Communities in the Stochastic Block Model With Application to Clustering with a Faulty Oracle—0
Efficient graph convolution for joint node representation learning and clusteringCode1
Matrix Completion with Hierarchical Graph Side Information—0
Persistent Homological State-Space Estimation of Functional Human Brain Networks at RestCode1
Scalable Deep Graph Clustering with Random-walk based Self-supervised Learning—0
Deep Graph Clustering via Dual Correlation ReductionCode1
Multilayer Graph Contrastive Clustering Network—0
RepBin: Constraint-based Graph Representation Learning for Metagenomic BinningCode1
A Modular Framework for Centrality and Clustering in Complex Networks—0
Deep Attention-guided Graph Clustering with Dual Self-supervisionCode1
Learning Co-segmentation by Segment Swapping for Retrieval and DiscoveryCode1
Multi-view Contrastive Graph ClusteringCode1
Robust Correlation Clustering with Asymmetric Noise—0
Self-supervised Contrastive Attributed Graph Clustering—0
Graphon based Clustering and Testing of Networks: Algorithms and TheoryCode0
Weakly Supervised Graph Clustering—0
Cluster Attack: Query-based Adversarial Attacks on Graphs with Graph-Dependent PriorsCode0
Self-Supervised Metric Learning With Graph Clustering For Speaker DiarizationCode0
RAMA: A Rapid Multicut Algorithm on GPUCode1
Attention-driven Graph Clustering NetworkCode1
Scalable Community Detection via Parallel Correlation ClusteringCode0
Rethinking Graph Auto-Encoder Models for Attributed Graph ClusteringCode1
Deep attributed graph clustering with self-separation regularization and parameter-free cluster estimation—0
Template-Based Graph ClusteringCode0
Latent structure blockmodels for Bayesian spectral graph clusteringCode0
Federated Graph Classification over Non-IID GraphsCode1
Structure-Aware Face Clustering on a Large-Scale Graph With 107 NodesCode1
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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