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20162025
most citedHypergraph reconstruction from noisy pairwise observations

15 citations · 48 across the 14 of their papers we have counts for

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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-ph2024

Governance as a complex, networked, democratic, satisfiability problem

Laurent Hébert-Dufresne, Nicholas W. Landry, Juniper Lovato +6

Democratic governments comprise a subset of a population whose goal is to produce coherent decisions, solving societal challenges while respecting the will of the people. New gover…

physics.soc-ph2022★ 10 cited

Compressing network populations with modal networks reveals structural diversity

Alec Kirkley, Alexis Rojas, Martin Rosvall +1

Analyzing relational data consisting of multiple samples or layers involves critical challenges: How many networks are required to capture the variety of structures in the data? An…

physics.soc-ph2020

Networks beyond pairwise interactions: structure and dynamics

Federico Battiston, Giulia Cencetti, Iacopo Iacopini +5

The complexity of many biological, social and technological systems stems from the richness of the interactions among their units. Over the past decades, a great variety of complex…

physics.soc-ph2019

Interacting contagions are indistinguishable from social reinforcement

Laurent Hébert-Dufresne, Samuel V. Scarpino, Jean-Gabriel Young

From fake news to innovative technologies, many contagions spread via a process of social reinforcement, where multiple exposures are distinct from prolonged exposure to a single s…

physics.soc-ph2018

Efficient sampling of spreading processes on complex networks using a composition and rejection algorithm

Guillaume St-Onge, Jean-Gabriel Young, Laurent Hébert-Dufresne +1

Efficient stochastic simulation algorithms are of paramount importance to the study of spreading phenomena on complex networks. Using insights and analytical results from network s…