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 …

Networks can describe the structure of a wide variety of complex systems by specifying
which pairs of entities in the system are connected. While such pairwise representations are …

Simple models of infectious diseases tend to assume random mixing of individuals, but real
interactions are not random pairwise encounters: they occur within various types of …

Network models for exchangeable arrays, including most stochastic block models, generate
dense graphs with a limited ability to capture many characteristics of real-world social and …

When studying interacting systems, computing their statistical properties is a fundamental
problem in various fields such as physics, applied mathematics, and machine learning …

The graph projection of a hypergraph is a simple graph with the same vertex set and with an
edge between each pair of vertices that appear in a hyperedge. We consider the problem of …

We propose a statistical model for graphs with a core-periphery structure. We give a precise
notion of what it means for a graph to have this structure, based on the sparsity properties of …

Graph datasets are frequently constructed by a projection of a bipartite graph, where two
nodes are connected in the projection if they share a common neighbor in the bipartite …

Résumé Alors que la pandémie de COVID-19 affecte le monde depuis presque deux ans, il
va sans dire qu'une meilleure compréhension des processus de contagion, de leur …

Modern models for complex networks have aimed to realistically describe empirical data:
they detect salient features, and they provide interpretations guided by statistical principles …