Zobrazeno 1 - 10
of 59
pro vyhledávání: '"Cliff, Oliver M."'
Autor:
Cajic, Pavle, Agius, Dominic, Cliff, Oliver M., Shine, James M., Lizier, Joseph T., Fulcher, Ben D.
The participation coefficient is a widely used metric of the diversity of a node's connections with respect to a modular partition of a network. An information-theoretic formulation of this concept of connection diversity, referred to here as partici
Externí odkaz:
http://arxiv.org/abs/2307.12556
Scientists have developed hundreds of techniques to measure the interactions between pairs of processes in complex systems. But these computational methods, from correlation coefficients to causal inference, rely on distinct quantitative theories tha
Externí odkaz:
http://arxiv.org/abs/2201.11941
Autor:
Svahn, Adam J., Chang, Sheryl L., Rockett, Rebecca J., Cliff, Oliver M., Wang, Qinning, Arnott, Alicia, Ramsperger, Marc, Sorrell, Tania C., Sintchenko, Vitali, Prokopenko, Mikhail
Publikováno v:
International Journal of Infectious Diseases, Volume 117 (2022), 65 - 73
Objectives: To enhance monitoring of high-burden foodborne pathogens, there is opportunity to combine pangenome data with network analysis. Methods: Salmonella enterica subspecies Enterica serovar Enteritidis isolates were referred to the New South W
Externí odkaz:
http://arxiv.org/abs/2201.05262
Publikováno v:
Frontiers in Public Health, 10 (2022)
An outbreak of the Delta (B.1.617.2) variant of SARS-CoV-2 that began around mid-June 2021 in Sydney, Australia, quickly developed into a nation-wide epidemic. The ongoing epidemic is of major concern as the Delta variant is more infectious than prev
Externí odkaz:
http://arxiv.org/abs/2107.06617
Background: To prevent future outbreaks of COVID-19, Australia is pursuing a mass-vaccination approach in which a targeted group of the population comprising healthcare workers, aged-care residents and other individuals at increased risk of exposure
Externí odkaz:
http://arxiv.org/abs/2103.07061
Publikováno v:
Nature Communications, 11: 5710, 2020
There is a continuing debate on relative benefits of various mitigation and suppression strategies aimed to control the spread of COVID-19. Here we report the results of agent-based modelling using a fine-grained computational simulation of the ongoi
Externí odkaz:
http://arxiv.org/abs/2003.10218
Publikováno v:
Phys. Rev. Research 3, 013145 (2021)
Inferring linear dependence between time series is central to our understanding of natural and artificial systems. Unfortunately, the hypothesis tests that are used to determine statistically significant directed or multivariate relationships from ti
Externí odkaz:
http://arxiv.org/abs/2003.03887
Autor:
Zachreson, Cameron, Fair, Kristopher M., Cliff, Oliver M., Harding, Nathan, Piraveenan, Mahendra, Prokopenko, Mikhail
Publikováno v:
Science Advances 4(12) (2018)
We examine salient trends of influenza pandemics in Australia, a rapidly urbanizing nation. To do so, we implement state-of-the-art influenza transmission and progression models within a large-scale stochastic computer simulation, generated using com
Externí odkaz:
http://arxiv.org/abs/1806.04001
Autor:
Cliff, Oliver M., Harding, Nathan, Piraveenan, Mahendra, Erten, E. Yagmur, Gambhir, Manoj, Prokopenko, Mikhail
In this paper we present ACEMod, an agent-based modelling framework for studying influenza epidemics in Australia. The simulator is designed to analyse the spatiotemporal spread of contagion and influenza spatial synchrony across the nation. The indi
Externí odkaz:
http://arxiv.org/abs/1806.02578
In this work, we are interested in structure learning for a set of spatially distributed dynamical systems, where individual subsystems are coupled via latent variables and observed through a filter. We represent this model as a directed acyclic grap
Externí odkaz:
http://arxiv.org/abs/1611.00549