84 citations · 325 across the 22 of their papers we have counts for
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stat.ML2013★ 84 cited
Non-parametric Bayesian modeling of complex networks
Mikkel N. Schmidt, Morten Mørup
Modeling structure in complex networks using Bayesian non-parametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observ…
stat.ML2013★ 5 cited
Nonparametric Bayesian models of hierarchical structure in complex networks
Mikkel N. Schmidt, Tue Herlau, Morten Mørup
Analyzing and understanding the structure of complex relational data is important in many applications including analysis of the connectivity in the human brain. Such networks can…
stat.ML2013★ 20 cited
The Infinite Degree Corrected Stochastic Block Model
Tue Herlau, Mikkel N. Schmidt, Morten Mørup
In Stochastic blockmodels, which are among the most prominent statistical models for cluster analysis of complex networks, clusters are defined as groups of nodes with statisticall…