1 citations · 2 across the 2 of their papers we have counts for
2 papers
stat.ME2022★ 1 cited
Stochastic Block Smooth Graphon Model
Benjamin Sischka, Göran Kauermann
The paper proposes the combination of stochastic blockmodels with smooth graphon models. The first allow for partitioning the set of individuals in a network into blocks which repr…
stat.ME2020★ 1 cited
Mixture Models and Networks -- Overview of Stochastic Blockmodelling
Giacomo De Nicola, Benjamin Sischka, Göran Kauermann
Mixture models are probabilistic models aimed at uncovering and representing latent subgroups within a population. In the realm of network data analysis, the latent subgroups of no…