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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 321–330 of 393 papers

Title	Date	Tasks	Status	Hype
COREclust: a new package for a robust and scalable analysis of complex data	May 25, 2018	ClusteringGraph Clustering	—Unverified	0
Searching for a Single Community in a Graph	May 24, 2018	ClusteringCommunity Detection	—Unverified	0
Tie-Line Characteristics based Partitioning for Distributed Optimization of Power Systems	May 24, 2018	ClusteringDistributed Optimization	—Unverified	0
Optimal Transport for structured data with application on graphs	May 23, 2018	ClusteringGraph Classification	CodeCode Available	2
Spectral clustering algorithms for the detection of clusters in block-cyclic and block-acyclic graphs	May 2, 2018	ClusteringGraph Clustering	—Unverified	0
The Power Mean Laplacian for Multilayer Graph Clustering	Mar 1, 2018	ClusteringGraph Clustering	CodeCode Available	0
Memetic Graph Clustering	Feb 20, 2018	ClusteringGraph Clustering	CodeCode Available	0
Adversarially Regularized Graph Autoencoder for Graph Embedding	Feb 13, 2018	ClusteringDecoder	CodeCode Available	1
A Theoretical Investigation of Graph Degree as an Unsupervised Normality Measure	Jan 24, 2018	Anomaly DetectionClustering	—Unverified	0
Learning Networks from Random Walk-Based Node Similarities	Jan 23, 2018	Anomaly DetectionClustering	CodeCode Available	0

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All datasets Citeseer Cora Pubmed Biase et al Bozec et al Deng et al Goolam et al Pollen et al Treutlein et al Yan et al

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	R-DGAE	ACC	70.5	—	Unverified
2	R-GMM-VGAE	ACC	68.9	—	Unverified
3	AGC	ACC	67	—	Unverified
4	RWR-GAE	ACC	61.6	—	Unverified
5	RWR-VGAE	ACC	61.3	—	Unverified
6	ARGE	ACC	57.3	—	Unverified
7	ARVGE	ACC	54.4	—	Unverified
8	GAE	ACC	40.8	—	Unverified
9	DAEGC+GSCAN†	NMI	39.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	R-GMM-VGAE	ACC	76.7	—	Unverified
2	R-DGAE	ACC	73.7	—	Unverified
3	AGC	ACC	68.92	—	Unverified
4	RWR-VGAE	ACC	68.5	—	Unverified
5	RWR-GAE	ACC	66.9	—	Unverified
6	ARGE	ACC	64	—	Unverified
7	ARVGE	ACC	63.8	—	Unverified
8	GAE	ACC	59.6	—	Unverified
9	DAEGC+GSCAN†	NMI	52.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	R-GMM-VGAE	ACC	74	—	Unverified
2	RWR-VGAE	ACC	73.6	—	Unverified
3	RWR-GAE	ACC	72.6	—	Unverified
4	R-DGAE	ACC	71.4	—	Unverified
5	AGC	ACC	69.78	—	Unverified
6	VGAE	ACC	65.48	—	Unverified
7	DAEGC+GSCAN†	NMI	31.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Polaratio Consensus Clustering	Adjusted Rand Index	1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Polaratio Consensus Clustering	Adjusted Rand Index	0.57	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Polaratio Consensus Clustering	Adjusted Rand Index	0.46	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Polaratio Consensus Clustering	Adjusted Rand Index	0.91	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Polaratio Consensus Clustering	Adjusted Rand Index	0.95	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Polaratio Consensus Clustering	Adjusted Rand Index	0.81	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Polaratio Consensus Clustering	Adjusted Rand Index	0.81	—	Unverified