activity
20082026
most citedAdaptive networks: coevolution of disease and topology

215 citations · 1.8k across the 55 of their papers we have counts for

collaborators

59 papers

physics.soc-ph2026

The impact of behavioral homophily and conformity on epidemic spreading in networks with large groups

Olivier Ribordy, Clara Granell, Guillaume St-Onge +3

Understanding how social behavior influences epidemic dynamics has become a central focus in mathematical epidemiology. In particular, \textit{behavioral homophily} (the tendency o…

physics.soc-ph2026

Simpson's paradox explains the ubiquity of nonlinear, threshold, and complex contagions

Laurent Hébert-Dufresne, Antoine Allard, Jean-Gabriel Young +2

Complex contagions describe systems where the probability or rate of contagious transmission is a nonlinear function of the exposure to contagious agents. These models were first s…

physics.soc-ph2025★ 1 cited

One pathogen does not an epidemic make: A review of interacting contagions, diseases, beliefs, and stories

Laurent Hébert-Dufresne, Yong-Yeol Ahn, Antoine Allard +15

From pathogens and computer viruses to genes and memes, contagion models have found widespread utility across the natural and social sciences. Despite their success and breadth of…

physics.soc-ph2023

Modeling critical connectivity constraints in random and empirical networks

Laurent Hébert-Dufresne, Márton Pósfai, Antoine Allard

Random networks are a powerful tool in the analytical modeling of complex networks as they allow us to write approximate mathematical models for diverse properties and behaviors of…

physics.soc-ph2023

The D-Mercator method for the multidimensional hyperbolic embedding of real networks

Robert Jankowski, Antoine Allard, Marián Boguñá +1

One of the pillars of the geometric approach to networks has been the development of model-based mapping tools that embed real networks in its latent geometry. In particular, the t…

physics.soc-ph2023

Geometric description of clustering in directed networks

Antoine Allard, M. Ángeles Serrano, Marián Boguñá

First principle network models are crucial to make sense of the intricate topology of real complex networks. While modeling efforts have been quite successful in undirected network…