We investigate dfferent mean-field-like approximations for stochastic dynamics on graphs, within the framework of a cluster-variational approach. In analogy with its equilibrium counterpart, this approach allows one to give a unified view of various (previously known) approximation schemes, and suggests quite a systematic way to improve the level of accuracy. We compare the different approximations with Monte Carlo simulations on a reversible (susceptible-infected-susceptible) discrete-time epidemic-spreading model on random graphs.
Variational approximations for stochastic dynamics on graphs / Pelizzola, Alessandro; Pretti, Marco. - In: JOURNAL OF STATISTICAL MECHANICS: THEORY AND EXPERIMENT. - ISSN 1742-5468. - ELETTRONICO. - 2017:7(2017), pp. 073406-1-073406-29. [10.1088/1742-5468/aa7a40]
Variational approximations for stochastic dynamics on graphs
PELIZZOLA, ALESSANDRO;PRETTI, MARCO
2017
Abstract
We investigate dfferent mean-field-like approximations for stochastic dynamics on graphs, within the framework of a cluster-variational approach. In analogy with its equilibrium counterpart, this approach allows one to give a unified view of various (previously known) approximation schemes, and suggests quite a systematic way to improve the level of accuracy. We compare the different approximations with Monte Carlo simulations on a reversible (susceptible-infected-susceptible) discrete-time epidemic-spreading model on random graphs.File | Dimensione | Formato | |
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Pelizzola_2017_J._Stat._Mech._2017_073406.pdf
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https://hdl.handle.net/11583/2677736
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