SOTAVerified

Community Detection

Community Detection is one of the fundamental problems in network analysis, where the goal is to find groups of nodes that are, in some sense, more similar to each other than to the other nodes.

Source: Randomized Spectral Clustering in Large-Scale Stochastic Block Models

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 251–275 of 919 papers

TitleStatusHype
Hypergraph Artificial Benchmark for Community Detection (h-ABCD)Code0
Overlapping Community Detection using Dynamic Dilated Aggregation in Deep Residual GCNCode0
Implicit models, latent compression, intrinsic biases, and cheap lunches in community detection—0
Detecting Propagators of Disinformation on Twitter Using Quantitative Discursive AnalysisCode0
Cognitive modelling with multilayer networks: Insights, advancements and future challenges—0
Trading off Quality for Efficiency of Community Detection: An Inductive Method across Graphs—0
Towards Direct Comparison of Community Structures in Social Networks—0
Community Detection in Multi-frequency EEG Networks—0
Exact Recovery of Community Detection in dependent Gaussian Mixture Models—0
A cost-based multi-layer network approach for the discovery of patient phenotypes—0
Bayan Algorithm: Detecting Communities in Networks Through Exact and Approximate Optimization of Modularity—0
An efficient approach for nonconvex semidefinite optimization via customized alternating direction method of multipliers—0
Dynamic Network Sampling for Community Detection—0
Community Detection in the Hypergraph SBM: Exact Recovery Given the Similarity Matrix—0
META-CODE: Community Detection via Exploratory Learning in Topologically Unknown Networks—0
Predicting the Biological Classification of Cell-Cycle Regulated Genes of Saccharomyces cerevisiae using Community Detection Algorithms on Gene Co-expression Networks—0
Network analysis of a complex disease: the gut microbiota in the inflammatory bowel disease case—0
GSim: A Graph Neural Network based Relevance Measure for Heterogeneous Graphs—0
Network strategies to study Epstein-Barr virus associated carcinomas and potential etiological mechanisms for oncogenesis—0
20 years of network community detection—0
Minimax Rates for Robust Community Detection—0
Communities in C.elegans connectome through the prism of non-backtracking walksCode0
Edge Augmentation on Disconnected Graphs via Eigenvalue Elevation—0
Signed Network Embedding with Application to Simultaneous Detection of Communities and Anomalies—0
GCN-based Multi-task Representation Learning for Anomaly Detection in Attributed Networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GNNAccuracy-NE2—Unverified
2CommunityGANF1-score0.09—Unverified
3Ego-SplittingF1-score0.04—Unverified
#ModelMetricClaimedVerifiedStatus
1EdMotNMI0.42—Unverified
2CDNMFNMI0.4—Unverified
#ModelMetricClaimedVerifiedStatus
1CDNMFACC0.48—Unverified
#ModelMetricClaimedVerifiedStatus
1CommunityGANF1-Score0.15—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.56—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.69—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.65—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.68—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.71—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.57—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.86—Unverified
#ModelMetricClaimedVerifiedStatus
1Smooth GEMSEC 2Modularity0.85—Unverified
#ModelMetricClaimedVerifiedStatus
1CDNMFACC0.67—Unverified