7 citations · 18 across the 15 of their papers we have counts for
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math.PR2014
Asymptotic description of stochastic neural networks. II - Characterization of the limit law
Olivier Faugeras, James MacLaurin
We continue the development, started in of the asymptotic description of certain stochastic neural networks. We use the Large Deviation Principle (LDP) and the good rate function H…
math.PR2014
Asymptotic description of stochastic neural networks. I - existence of a Large Deviation Principle
Olivier Faugeras, James MacLaurin
We study the asymptotic law of a network of interacting neurons when the number of neurons becomes infinite. The dynamics of the neurons is described by a set of stochastic differe…
math.PR2014★ 1 cited
Large Deviations of a Spatially-Stationary Network of Interacting Neurons
Olivier Faugeras, James MacLaurin
In this work we determine a process-level Large Deviation Principle (LDP) for a model of interacting neurons indexed by a lattice . The neurons are subject to noise,…