Zobrazeno 1 - 10
of 248
pro vyhledávání: '"Antoine Allard"'
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-15 (2024)
Abstract 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 the structure of interaction from temporal observations. Here,
Externí odkaz:
https://doaj.org/article/36ae7220edeb4ff080790c58833c7daa
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-13 (2023)
Abstract The network reconstruction task aims to estimate a complex system’s structure from various data sources such as time series, snapshots, or interaction counts. Recent work has examined this problem in networks whose relationships involve pr
Externí odkaz:
https://doaj.org/article/6e5624de8a40440c900d51bcb365a824
Publikováno v:
Nature Communications, Vol 14, Iss 1, Pp 1-11 (2023)
Abstract 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 tool Mercator embeds networks into the hyperbolic plane. Howev
Externí odkaz:
https://doaj.org/article/00affdbfcd1a45faa86b160122220e8e
Autor:
Guillaume St-Onge, Iacopo Iacopini, Vito Latora, Alain Barrat, Giovanni Petri, Antoine Allard, Laurent Hébert-Dufresne
Publikováno v:
Communications Physics, Vol 5, Iss 1, Pp 1-16 (2022)
Group interactions can dramatically alter social contagion dynamics and lead to the emergence of new phenomena like abrupt transitions and critical mass effects. The authors develop an approximate master equation framework to analytically describe co
Externí odkaz:
https://doaj.org/article/1e157d6a7bc643c599ae929bb91d021c
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-11 (2021)
Prediction of contagion dynamics is of relevance for epidemic and social complex networks. Murphy et al. propose a data-driven approach based on deep learning which allows to learn mechanisms governing network dynamics and make predictions beyond the
Externí odkaz:
https://doaj.org/article/dd478dea3f164012a35d9b2dec8c9bb8
Publikováno v:
Physical Review Research, Vol 4, Iss 2, p L022029 (2022)
Cells have evolved efficient strategies to probe their surroundings and navigate through complex environments. From metastatic spread in the body to swimming cells in porous materials, escape through narrow constrictions—a key component of any stru
Externí odkaz:
https://doaj.org/article/69456249bd754d7a97feb764f45dee47
Publikováno v:
Journal of Physics: Complexity, Vol 4, Iss 3, p 035002 (2023)
Knowledge silos emerge when structural properties of organizational interaction networks limit the diffusion of information. These structural barriers are known to take many forms at different scales—hubs in otherwise sparse organizations, large de
Externí odkaz:
https://doaj.org/article/bcd22e23e23240b7a303ea7f37b120b1
Autor:
Benjamin M Althouse, Edward A Wenger, Joel C Miller, Samuel V Scarpino, Antoine Allard, Laurent Hébert-Dufresne, Hao Hu
Publikováno v:
PLoS Biology, Vol 18, Iss 11, p e3000897 (2020)
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the etiological agent of the Coronavirus Disease 2019 (COVID-19) disease, has moved rapidly around the globe, infecting millions and killing hundreds of thousands. The basic reproduction n
Externí odkaz:
https://doaj.org/article/084a51b695834316b7e11773322c19b3
Autor:
Andrea J. Allen, Mariah C. Boudreau, Nicholas J. Roberts, Antoine Allard, Laurent Hébert-Dufresne
Publikováno v:
Physical Review Research, Vol 4, Iss 1, p 013123 (2022)
The interplay of biological, social, structural, and random factors makes disease forecasting extraordinarily complex. The course of an epidemic exhibits average growth dynamics determined by features of the pathogen and the population, yet also feat
Externí odkaz:
https://doaj.org/article/cf6afacea86f4e959cb69a934a580e54
Autor:
Antoine Allard, M Ángeles Serrano
Publikováno v:
PLoS Computational Biology, Vol 16, Iss 2, p e1007584 (2020)
Connectomes are spatially embedded networks whose architecture has been shaped by physical constraints and communication needs throughout evolution. Using a decentralized navigation protocol, we investigate the relationship between the structure of t
Externí odkaz:
https://doaj.org/article/f79a5c5343404711a1cf40c0a01ab1e6