Latent space models (LSMs) are frequently used to model network data by
...
Continuous time network data have been successfully modeled by multivari...
Latent space models are popular for analyzing dynamic network data. We
p...
Dynamic multilayer networks frequently represent the structure of multip...
Dynamic networks are used in a variety of fields to represent the struct...
Embedding dyadic data into a latent space has long been a popular approa...
The formation of social networks and the evolution of their structures h...
It is often of interest to perform clustering on longitudinal data, yet ...
Longitudinal binary relational data can be better understood by implemen...
The evolution of communities in dynamic (time-varying) network data is a...
Higher-order motif structures and multi-vertex interactions are becoming...
Motivated by multi-subject experiments in neuroimaging studies, we devel...
Heterogeneous networks are networks consisting of different types of nod...
We consider the problem of estimating a consensus community structure by...
We present a method based on the orthogonal symmetric non-negative matri...
In recent years there has been an increased interest in statistical anal...