activity
20182020
most citedDetecting structural perturbations from time series with deep learning

2 citations · 2 across the 1 of their papers we have counts for

collaborators

9 papers

physics.soc-ph2020

Network comparison and the within-ensemble graph distance

Harrison Hartle, Brennan Klein, Stefan McCabe +4

Quantifying the differences between networks is a challenging and ever-present problem in network science. In recent years a multitude of diverse, ad hoc solutions to this problem…

physics.soc-ph20202 cited

Detecting structural perturbations from time series with deep learning

Edward Laurence, Charles Murphy, Guillaume St-Onge +2

Small disturbances can trigger functional breakdowns in complex systems. A challenging task is to infer the structural cause of a disturbance in a networked system, soon enough to…

nlin.AO2020

Threefold way to the dimension reduction of dynamics on networks: an application to synchronization

Vincent Thibeault, Guillaume St-Onge, Louis J. Dubé +1

Several complex systems can be modeled as large networks in which the state of the nodes continuously evolves through interactions among neighboring nodes, forming a high-dimension…

physics.soc-ph2020

Master equation analysis of mesoscopic localization in contagion dynamics on higher-order networks

Guillaume St-Onge, Vincent Thibeault, Antoine Allard +2

Simple models of infectious diseases tend to assume random mixing of individuals, but real interactions are not random pairwise encounters: they occur within various types of gathe…

physics.soc-ph2020

Social confinement and mesoscopic localization of epidemics on networks

Guillaume St-Onge, Vincent Thibeault, Antoine Allard +2

Recommendations around epidemics tend to focus on individual behaviors, with much less efforts attempting to guide event cancellations and other collective behaviors since most mod…

cs.SI2019

Inference for growing trees

George T. Cantwell, Guillaume St-Onge, Jean-Gabriel Young

One can often make inferences about a growing network from its current state alone. For example, it is generally possible to determine how a network changed over time or pick among…