All beauty, richness and harmony in the emergent dynamics of a complex system largely
depend on the specific way in which its elementary components interact. The last twenty-five …

Recent developments in complex systems have witnessed that many real-world scenarios,
successfully represented as networks, are not always restricted to binary interactions but …

Hypergraph neural networks (HNNs) using neural networks to encode hypergraphs provide
a promising way to model higher-order relations in data and further solve relevant prediction …

Going beyond networks, to include higher-order interactions of arbitrary sizes, is a major
step to better describe complex systems. In the resulting hypergraph representation, tools to …

We investigate consensus dynamics on temporal hypergraphs that encode network systems
with time-dependent, multiway interactions. We compare these consensus processes with …

Representing social systems as networks, starting from the interactions between individuals,
sheds light on the mechanisms governing their dynamics. However, networks encode only …

Core-periphery detection is a key task in exploratory network analysis where one aims to
find a core, a set of nodes well connected internally and with the periphery, and a periphery …

Dynamical systems on hypergraphs can display a rich set of behaviors not observable for
systems with pairwise interactions. Given a distributed dynamical system with a putative …

People's opinions evolve with time as they interact with their friends, family, colleagues, and
others. In the study of opinion dynamics on networks, one often encodes interactions …

We present a unifying Perron--Frobenius theory for nonlinear spectral problems defined in
terms of nonnegative tensors. By using the concept of tensor shape partition, our results …