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20082026
most citedAdaptive networks: coevolution of disease and topology

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

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8 papers · 1 filter

cond-mat.stat-mech2022★ 8 cited

Duality between predictability and reconstructability in complex systems

Charles Murphy, Vincent Thibeault, Antoine Allard +1

Predicting the evolution of a large system of units using its structure of interaction is a fundamental problem in complex system theory. And so is the problem of reconstructing th…

cond-mat.stat-mech2015★ 30 cited

General and exact approach to percolation on random graphs

Antoine Allard, Laurent Hébert-Dufresne, Jean-Gabriel Young +1

We present a comprehensive and versatile theoretical framework to study site and bond percolation on clustered and correlated random graphs. Our contribution can be summarized in t…

cond-mat.stat-mech2013★ 7 cited

Coexistence of phases and the observability of random graphs

Antoine Allard, Laurent Hébert-Dufresne, Jean-Gabriel Young +1

In a recent Letter, Yang et al. [Phys. Rev. Lett. 109, 258701 (2012)] introduced the concept of observability transitions: the percolation-like emergence of a macroscopic observabl…

cond-mat.stat-mech2012★ 29 cited

Bond percolation on a class of correlated and clustered random graphs

Antoine Allard, Laurent Hébert-Dufresne, Pierre-André Noël +2

We introduce a formalism for computing bond percolation properties of a class of correlated and clustered random graphs. This class of graphs is a generalization of the Configurati…

cond-mat.stat-mech2012★ 8 cited

Exact solution of bond percolation on small arbitrary graphs

Antoine Allard, Laurent Hébert-Dufresne, Pierre-André Noël +2

We introduce a set of iterative equations that exactly solves the size distribution of components on small arbitrary graphs after the random removal of edges. We also demonstrate h…

cond-mat.stat-mech2011★ 19 cited

Propagation on networks: an exact alternative perspective

Pierre-André Noël, Antoine Allard, Laurent Hébert-Dufresne +2

By generating the specifics of a network structure only when needed (on-the-fly), we derive a simple stochastic process that exactly models the time evolution of susceptible-infect…