Recent decades have seen a rise in the use of physics methods to study different societal
phenomena. This development has been due to physicists venturing outside of their …

Community detection in networks is one of the most popular topics of modern network
science. Communities, or clusters, are usually groups of vertices having higher probability of …

Link prediction is a key problem for network-structured data. Link prediction heuristics use
some score functions, such as common neighbors and Katz index, to measure the likelihood …

An animal's nervous system changes as its body grows from birth to adulthood and its
behaviours mature,,,,,,–. The form and extent of circuit remodelling across the connectome is …

The brain is characterized by heterogeneous patterns of structural connections supporting
unparalleled feats of cognition and a wide range of behaviours. New non-invasive imaging …

There have been rapid developments in model-based clustering of graphs, also known as
block modelling, over the last ten years or so. We review different approaches and …

For many networks of scientific interest we know both the connections of the network and
information about the network nodes, such as the age or gender of individuals in a social …

In this paper, we propose a next-generation link prediction method, Weisfeiler-Lehman
Neural Machine (WLNM), which learns topological features in the form of graph patterns that …

This chapter describes the basic variants of the stochastic blockmodel (SBM), and a
consistent Bayesian formulation that allows readers to infer them from data. The focus is on …

We provide the first information theoretical tight analysis for inference of latent community
structure given a sparse graph along with high dimensional node covariates, correlated with …