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

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Showing 601–650 of 919 papers

TitleStatusHype
Inference of hidden structures in complex physical systems by multi-scale clustering—0
Inference via Message Passing on Partially Labeled Stochastic Block Models—0
Infinite Edge Partition Models for Overlapping Community Detection and Link Prediction—0
Information Retrieval and Extraction on COVID-19 Clinical Articles Using Graph Community Detection and Bio-BERT Embeddings—0
Information-theoretic Limits for Community Detection in Network Models—0
Information Theoretic Limits of Exact Recovery in Sub-hypergraph Models for Community Detection—0
Integration of graph clustering with ant colony optimization for feature selection—0
Intelligent Anti-Money Laundering Solution Based upon Novel Community Detection in Massive Transaction Networks on Spark—0
International Trade Network: Country centrality and COVID-19 pandemic—0
Introducing the modularity graph: an application to brain functional networks—0
Inverse Graph Identification: Can We Identify Node Labels Given Graph Labels?—0
Investigating internal migration with network analysis and latent space representations: An application to Turkey—0
Ising-Based Louvain Method: Clustering Large Graphs with Specialized Hardware—0
Joint community and anomaly tracking in dynamic networks—0
Joint Content-Context Analysis of Scientific Publications: Identifying Opportunities for Collaboration in Cognitive Science—0
Joint Content-Context Analysis of Scientific Publications: Identifying Opportunities for Collaboration in Cognitive Science—0
KAN KAN Buff Signed Graph Neural Networks?—0
Kernel k-Groups via Hartigan's Method—0
Knowledge Graph semantic enhancement of input data for improving AI—0
Laplacian Mixture Modeling for Network Analysis and Unsupervised Learning on Graphs—0
Large Language Models Meet Graph Neural Networks: A Perspective of Graph Mining—0
Large-scale nonlinear Granger causality for inferring directed dependence from short multivariate time-series data—0
Latent Geometry Inspired Graph Dissimilarities Enhance Affinity Propagation Community Detection in Complex Networks—0
Latent heterogeneous multilayer community detection—0
Leaders, Followers, and Community Detection—0
Learning Communities from Equilibria of Nonlinear Opinion Dynamics—0
Learning Communities in the Presence of Errors—0
LEARNING GUARANTEES FOR GRAPH CONVOLUTIONAL NETWORKS ON THE STOCHASTIC BLOCK MODEL—0
Learning higher-order sequential structure with cloned HMMs—0
Learning Influence-Receptivity Network Structure with Guarantee—0
Learning Latent Block Structure in Weighted Networks—0
Learning Mixed Membership Community Models in Social Tagging Networks through Tensor Methods—0
Learning multi-faceted representations of individuals from heterogeneous evidence using neural networks—0
Leiden-Fusion Partitioning Method for Effective Distributed Training of Graph Embeddings—0
Linear-Sample Learning of Low-Rank Distributions—0
Local Algorithms for Block Models with Side Information—0
Localizing and Assessing Node Significance in Default Mode Network using Sub-Community Detection in Mild Cognitive Impairment—0
Locally Boosted Graph Aggregation for Community Detection—0
Local Network Community Detection with Continuous Optimization of Conductance and Weighted Kernel K-Means—0
LoCEC: Local Community-based Edge Classification in Large Online Social Networks—0
Logistic Regression Augmented Community Detection for Network Data with Application in Identifying Autism-Related Gene Pathways—0
Low-Rank Projections of GCNs Laplacian—0
Machine learning meets network science: dimensionality reduction for fast and efficient embedding of networks in the hyperbolic space—0
Mapping higher-order network flows in memory and multilayer networks with Infomap—0
Mapping Hymns and Organizing Concepts in the Rigveda: Quantitatively Connecting the Vedic Suktas—0
Matched bipartite block model with covariates—0
Matrix Concentration for Random Signed Graphs and Community Recovery in the Signed Stochastic Block Model—0
Matrix Factorization in Tropical and Mixed Tropical-Linear Algebras—0
MCMC Louvain for Online Community Detection—0
Mean Field for the Stochastic Blockmodel: Optimization Landscape and Convergence Issues—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