Our papers are the official record of our discoveries. They allow others to build on and apply our work. Each paper is the result of many months of research, so we make a special effort to make them clear, beautiful and inspirational, and publish them in leading journals.
Inference from single snapshots of temporal networks can misleadingly group communities if the links between snapshots are correlated.
The spectral density of graph ensembles provides an exact solution to the graph partitioning problem and helps detect community structure.
The community matrix of a complex ecosystem captures the population dynamics of interacting species and transitions to unstable abundances.
A new tool derived from information theory quantitatively identifies trees, hierarchies and community structures within complex networks.