The complexity of many biological, social and technological systems stems from the richness
of the interactions among their units. Over the past decades, a variety of complex systems …

Social network based applications have experienced exponential growth in recent years.
One of the reasons for this rise is that this application domain offers a particularly fertile …

Graph deep learning models, such as graph convolutional networks (GCN) achieve
remarkable performance for tasks on graph data. Similar to other types of deep models …

The stochastic block model (SBM) is a random graph model with planted clusters. It is widely
employed as a canonical model to study clustering and community detection, and provides …

Networks provide a powerful formalism for modeling complex systems by using a model of
pairwise interactions. But much of the structure within these systems involves interactions …

The growth of social media over the last decade has revolutionized the way individuals
interact and industries conduct business. Individuals produce data at an unprecedented rate …

Reporting specific modelling methods and metadata is essential to the reproducibility of
ecological studies, yet guidelines rarely exist regarding what information should be noted …

Research on growth of innovations introduced to the market has gradually shifted its focus
from aggregate-level diffusion to exploring how growth is influenced by a given social …

New phase transition phenomena have recently been discovered for the stochastic block
model, for the special case of two non-overlapping symmetric communities. This gives raise …

Controlling complex networks is of paramount importance in science and engineering.
Despite the recent development of structural controllability theory, we continue to lack a …