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Mean-field limit of age and leaky memory dependent Hawkes processes

Schmutz, Valentin; (2022) Mean-field limit of age and leaky memory dependent Hawkes processes. Stochastic Processes and their Applications , 149 pp. 39-59. 10.1016/j.spa.2022.03.006. Green open access

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Abstract

We propose a mean-field model of interacting point processes where each process has a memory of the time elapsed since its last event (age) and its recent past (leaky memory), generalizing Age-dependent Hawkes processes. The model is motivated by interacting nonlinear Hawkes processes with Markovian self-interaction and networks of spiking neurons with adaptation and short-term synaptic plasticity. By proving propagation of chaos and using a path integral representation for the law of the limit process, we show that, in the mean-field limit, the empirical measure of the system follows a multidimensional nonlocal transport equation.

Type: Article
Title: Mean-field limit of age and leaky memory dependent Hawkes processes
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.spa.2022.03.006
Publisher version: https://doi.org/10.1016/j.spa.2022.03.006
Language: English
Additional information: © 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Hawkes process, Mean-field approximation, Nonlocal transport equation, Propagation of chaos, Erlang kernel, Short-term synaptic plasticity
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10178707
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