1 code implementation • 18 Jan 2021 • Guillaume St-Onge, Hanlin Sun, Antoine Allard, Laurent Hébert-Dufresne, Ginestra Bianconi
The colocation of individuals in different environments is an important prerequisite for exposure to infectious diseases on a social network.
Physics and Society Adaptation and Self-Organizing Systems
2 code implementations • 6 Aug 2020 • Harrison Hartle, Brennan Klein, Stefan McCabe, Alexander Daniels, Guillaume St-Onge, Charles Murphy, Laurent Hébert-Dufresne
Quantifying the differences between networks is a challenging and ever-present problem in network science.
Physics and Society Social and Information Networks
no code implementations • 15 Jul 2020 • Blake J. M. Williams, Guillaume St-Onge, Laurent Hébert-Dufresne
Mathematical disease modelling has long operated under the assumption that any one infectious disease is caused by one transmissible pathogen spreading among a population.
1 code implementation • 9 Jun 2020 • Edward Laurence, Charles Murphy, Guillaume St-Onge, Xavier Roy-Pomerleau, Vincent Thibeault
Small disturbances can trigger functional breakdowns in complex systems.
no code implementations • 12 Mar 2020 • Guillaume St-Onge, Vincent Thibeault, Antoine Allard, Louis J. Dubé, Laurent Hébert-Dufresne
Recommendations around epidemics tend to focus on individual behaviors, with much less efforts attempting to guide event cancellations and other collective behaviors since most models lack the higher-order structure necessary to describe large gatherings.
Physics and Society Adaptation and Self-Organizing Systems
2 code implementations • 10 Oct 2019 • George T. Cantwell, Guillaume St-Onge, Jean-Gabriel Young
In principle one can reconstruct the past states of a growing network from only its current state.
Social and Information Networks Physics and Society
3 code implementations • 15 Aug 2018 • Guillaume St-Onge, Jean-Gabriel Young, Laurent Hébert-Dufresne, Louis J. Dubé
Efficient stochastic simulation algorithms are of paramount importance to the study of spreading phenomena on complex networks.
Physics and Society Social and Information Networks
no code implementations • 11 Jun 2018 • Jean-Gabriel Young, Guillaume St-Onge, Patrick Desrosiers, Louis J. Dubé
Mesoscopic pattern extraction (MPE) is the problem of finding a partition of the nodes of a complex network that maximizes some objective function.
1 code implementation • 25 Mar 2018 • Jean-Gabriel Young, Guillaume St-Onge, Edward Laurence, Charles Murphy, Laurent Hébert-Dufresne, Patrick Desrosiers
Network growth processes can be understood as generative models of the structure and history of complex networks.