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 301–350 of 393 papers

TitleStatusHype
Hermitian matrices for clustering directed graphs: insights and applications—0
Hierarchical Agglomerative Graph Clustering in Nearly-Linear Time—0
Higher-Order Spectral Clustering of Directed Graphs—0
Human Semantic Segmentation using Millimeter-Wave Radar Sparse Point Clouds—0
Hybrid Clustering based on Content and Connection Structure using Joint Nonnegative Matrix Factorization—0
Hyperedge Modeling in Hypergraph Neural Networks by using Densest Overlapping Subgraphs—0
Improved Dual Correlation Reduction Network—0
Improved Graph Clustering—0
Incorporating Higher-order Structural Information for Graph Clustering—0
Incremental Multi-graph Matching via Diversity and Randomness based Graph Clustering—0
Independence Promoted Graph Disentangled Networks—0
Influence-Based Mini-Batching for Graph Neural Networks—0
Information Recovery in Shuffled Graphs via Graph Matching—0
Integration of graph clustering with ant colony optimization for feature selection—0
JoBimText Visualizer: A Graph-based Approach to Contextualizing Distributional Similarity—0
KCoreMotif: An Efficient Graph Clustering Algorithm for Large Networks by Exploiting k-core Decomposition and Motifs—0
Multiway p-spectral graph cuts on Grassmann manifolds—0
L2F/INESC-ID at SemEval-2019 Task 2: Unsupervised Lexical Semantic Frame Induction using Contextualized Word Representations—0
Large Language Models and Knowledge Graphs for Astronomical Entity Disambiguation—0
Large Scale Video Representation Learning via Relational Graph Clustering—0
Layout-Graph Reasoning for Fashion Landmark Detection—0
Learning a Fast 3D Spectral Approach to Object Segmentation and Tracking over Space and Time—0
Learning Graph Embedding with Adversarial Training Methods—0
Learning Graph Representations by Dendrograms—0
Learning Uniform Clusters on Hypersphere for Deep Graph-level Clustering—0
Local Algorithms for Estimating Effective Resistance—0
Local Graph Clustering Beyond Cheeger's Inequality—0
Local Graph Clustering with Network Lasso—0
Local Graph Clustering with Noisy Labels—0
Lost in Discussion? Tracking Opinion Groups in Complex Political Discussions by the Example of the FOMC Meeting Transcriptions—0
Low-Rank Optimal Transport through Factor Relaxation with Latent Coupling—0
Low-Rank Riemannian Optimization on Positive Semidefinite Stochastic Matrices with Applications to Graph Clustering—0
Marginalized graph autoencoder for graph clustering—0
MaskClustering: View Consensus based Mask Graph Clustering for Open-Vocabulary 3D Instance Segmentation—0
Masked AutoEncoder for Graph Clustering without Pre-defined Cluster Number k—0
Matrix Completion with Hierarchical Graph Side Information—0
Mean Field Analysis of Personalized PageRank with Implications for Local Graph Clustering—0
Median evidential c-means algorithm and its application to community detection—0
Model-Free Optimal Control of Linear Multi-Agent Systems via Decomposition and Hierarchical Approximation—0
Model Reduction of Consensus Network Systems via Selection of Optimal Edge Weights and Nodal Time-Scales—0
Modularity aided consistent attributed graph clustering via coarsening—0
Modular Training of Neural Networks aids Interpretability—0
Monash-Summ@LongSumm 20 SciSummPip: An Unsupervised Scientific Paper Summarization Pipeline—0
Possibility results for graph clustering: A novel consistency axiom—0
BGC: Multi-Agent Group Belief with Graph Clustering—0
Multicuts and Perturb & MAP for Probabilistic Graph Clustering—0
Multi-factor Sequential Re-ranking with Perception-Aware Diversification—0
Multigraph Clustering for Unsupervised Coreference Resolution—0
Community Detection and Growth Potential Prediction Using the Stochastic Block Model and the Long Short-term Memory from Patent Citation Networks—0
Multilayer Graph Contrastive Clustering Network—0
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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