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Found 3 papers, 3 papers with code
Hypergraphs with node attributes: structure and inference
Many networked datasets with units interacting in groups of two or more, encoded with hypergraphs, are accompanied by extra information about nodes, such as the role of an individual in a workplace.
Sampling on networks: estimating spectral centrality measures and their impact in evaluating other relevant network measures
On the other hand, to demonstrate more broadly how sampling can impact the estimation of relevant network properties like centrality measures different than the one aimed at optimizing, community structure and node attribute distribution.
Social and Information Networks Data Analysis, Statistics and Probability Physics and Society
Sampling on networks: estimating eigenvector centrality on incomplete graphs
We develop a new sampling method to estimate eigenvector centrality on incomplete networks.
Social and Information Networks Data Analysis, Statistics and Probability Physics and Society
