
CRAN
 Referenced in 506 articles
[sw04351]
 clustering, etc. Please consult the R project homepage for further information. CRAN is a network...

Neural Network Toolbox
 Referenced in 175 articles
[sw07378]
 Neural Network Toolbox for applications such as data fitting, pattern recognition, clustering, timeseries prediction...

MCODE
 Referenced in 48 articles
[sw35748]
 protein interaction networks. Results: This paper describes a novel graph theoretic clustering algorithm, ”Molecular Complex ... connected regions in large proteinprotein interaction networks that may represent molecular complexes. The method ... algorithm has the advantage over other graph clustering methods of having a directed mode that ... rest of the network and allows examination of cluster interconnectivity, which is relevant for protein...

metafor
 Referenced in 31 articles
[sw12291]
 multiple endpoints, or other forms of clustering). Network metaanalyses and metaanalyses accounting...

NEURON
 Referenced in 181 articles
[sw03059]
 published network models with very different spike patterns exhibits superlinear speedup on Beowulf clusters ... magnitude makes practical the running of large network simulations that could otherwise not be explored...

latentnet
 Referenced in 18 articles
[sw10550]
 Fitting Latent Cluster Models for Networks with latentnet. latentnet is a package ... evaluate statistical latent position and cluster models for networks. Hoff, Raftery, and Handcock (2002) suggested ... approach to modeling networks based on positing the existence of an latent space of characteristics ... function to simulate networks from a latent position or latent position cluster model...

SAcluster
 Referenced in 9 articles
[sw06867]
 Clustering large attributed information networks: an efficient incremental computing approach In recent years, many information ... road networks, sensor networks, biological networks, etc. Graph clustering has shown its effectiveness in analyzing ... visualizing large networks. The goal of graph clustering is to partition vertices in a large...

BRITE
 Referenced in 34 articles
[sw03098]
 properties of generated network topologies (such power laws, path length and clustering coefficient). BRITE ... existing nodes; (2) incremental growth of the network; (3) geographical distribution of nodes...

ScaLAPACK
 Referenced in 410 articles
[sw00830]
 distributed memory messagepassing MIMD computers and networks of workstations supporting parallel virtual machine ... Intel series, TM CM5, clusters of workstations, and any system for which...

DistAl
 Referenced in 100 articles
[sw01746]
 pattern classification systems. A new constructive neural network learning algorithm (DistAl) based on interpattern ... Each neuron is designed to determine a cluster of training patterns belonging to the same...

gSkeletonClu
 Referenced in 3 articles
[sw30861]
 gSkeletonClu: DensityBased Network Clustering via StructureConnected Tree Division or Agglomeration. Community detection ... hubs and outliers. A recently proposed network clustering algorithm, SCAN, is effective and can overcome ... propose a novel densitybased network clustering algorithm, called gSkeletonClu (graphskeleton based clustering ... Connected Maximal Spanning Tree (CCMST), the network clustering problem is converted to finding coreconnected...

CFinder
 Referenced in 25 articles
[sw12379]
 clusters. These modules often overlap with each other and form a network of their...

CiteSpace
 Referenced in 8 articles
[sw39808]
 land of publications, decomposing a network into clusters, automatic labeling clusters with terms from citing ... temporal analyses of a variety of networks derived from scientific publications, including collaboration networks, author...

GREMLIN
 Referenced in 5 articles
[sw03276]
 research institutions are connected to a WANcluster via PVM 3.4.3. The secure shell protocol ... kind of heterogeneous Wide Area Network cluster...

Inccluster
 Referenced in 5 articles
[sw06866]
 Clustering large attributed information networks: an efficient incremental computing approach In recent years, many information ... road networks, sensor networks, biological networks, etc. Graph clustering has shown its effectiveness in analyzing ... visualizing large networks. The goal of graph clustering is to partition vertices in a large...

LAMG
 Referenced in 28 articles
[sw06551]
 learning; spectral clustering of images, genetic data, and web pages; transportation network flows; electrical resistor...

NodeXL
 Referenced in 7 articles
[sw04183]
 Interactive network exploration to derive insights: filtering, clustering, grouping, and simplification The growing importance ... decisions. Since networks are often complex and cluttered, strategies for effective filtering, clustering, grouping ... finding key nodes and links, surprising clusters, important groups, or meaningful patterns. We describe readability ... source network analysis tool, and show examples from our research. While filtering, clustering, and grouping...

VNDS
 Referenced in 6 articles
[sw07586]
 variable neighborhood search Finding communities or clusters, in networks, or graphs, has been the subject ... consists in maximizing the sum for all clusters of the number of inner edges minus...

LPAm+
 Referenced in 6 articles
[sw07587]
 variable neighborhood search Finding communities or clusters, in networks, or graphs, has been the subject ... consists in maximizing the sum for all clusters of the number of inner edges minus...

SpectralNet
 Referenced in 4 articles
[sw26162]
 SpectralNet: Spectral Clustering using Deep Neural Networks. Spectral clustering is a leading and popular technique ... approach to spectral clustering that overcomes the above shortcomings. Our network, which we call SpectralNet ... their associated graph Laplacian matrix and subsequently clusters them. We train SpectralNet using a procedure ... output layer, allow us to keep the network output orthogonal. Moreover, the map learned...