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Browsing MACSI - Mathematics Application Consortium for Science & Industry by Subject "model"

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Browsing MACSI - Mathematics Application Consortium for Science & Industry by Subject "model"

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  • Gleeson, James P. (American Physical Society, 2013)
    A wide class of binary-state dynamics on networks-including, for example, the voter model, the Bass diffusion model, and threshold models-can be described in terms of transition rates (spin-flip probabilities) that depend ...
  • Melnik, Sergey; Porter, Mason A; Mucha, Peter J; Gleeson, James P. (American Institute of Physics, 2014)
    We develop a new ensemble of modular random graphs in which degree-degree correlations can be different in each module, and the inter-module connections are defined by the joint degree-degree distribution of nodes for each ...
  • Fowler, Andrew C.; Kopteva, Natalia; Oakley, Charles (Society for Industrial and Applied Mathematics, 2006)
    We consider a deterministic model of landscape evolution through the mechanism of overland flow over an erodible substrate, using the St. Venant equations of hydraulics together with the Exner equation for hillslope erosion. ...
  • Hurd, Thomas R; Gleeson, James P.; Melnik, Sergey (Public Library of Science, 2017)
    We introduce a probabilistic framework that represents stylized banking networks with the aim of predicting the size of contagion events. Most previous work on random financial networks assumes independent connections ...
  • Gleeson, James P. (American Physical Society, 2011)
    Binary-state dynamics (such as the susceptible-infected-susceptible (SIS) model of disease spread, or Glauber spin dynamics) on random networks are accurately approximated using master equations. Standard mean-field and ...
  • Fennell, Peter G.; Melnik, Sergey; Gleeson, James P. (American Physical Society, 2016)
    Continuous-time Markov process models of contagions are widely studied, not least because of their utility in predicting the evolution of real-world contagions and in formulating control measures. It is often the case, ...
  • Melnik, Sergey; Ward, Jonathan A; Gleeson, James P.; Porter, Mason A (American Institute of Physics, 2013)
    The spread of ideas across a social network can be studied using complex contagion models, in which agents are activated by contact with multiple activated neighbors. The investigation of complex contagions can provide ...

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