It is a fundamental challenge to understand how the function of a network is related to its
structural organization. Adaptive dynamical networks represent a broad class of systems that …

Networks of coupled dynamical units give rise to collective dynamics such as the
synchronization of oscillators or neurons in the brain. The ability of the network to adapt …

Adaptive (or co-evolutionary) network dynamics, ie, when changes of the network/graph
topology are coupled with changes in the node/vertex dynamics, can give rise to rich and …

Many science phenomena are modelled as interacting particle systems (IPS) coupled on
static networks. In reality, network connections are far more dynamic. Connections among …

Models of coupled oscillator networks play an important role in describing collective
synchronization dynamics in biological and technological systems. The Kuramoto model …

In this article, we study the large-population limit of interacting particle systems posed on
weighted random graphs. In that aim, we introduce a general framework for the construction …

A particle system is said to be non-exchangeable if two particles cannot be exchanged
without modifying the overall dynamics. Because of this property, the classical mean-field …

We introduce an optimal transport topology on the space of probability measures over a fiber
bundle, which penalizes the transport cost from one fiber to another. For simplicity, we …

We study the mean-field limit of a model of biological neuron networks based on the so-
called stochastic integrate-and-fire (IF) dynamics. Our approach allows to derive a …

We are investigating deterministic SIS dynamics on large networks starting from only a few
infected individuals. Under mild assumptions we show that any two epidemic curves–on the …