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We study a multivariate, non-linear Hawkes process $Z^N$ on the complete graph with $N$ nodes. Each vertex is either excitatory (probability $p$) or inhibitory (probability $1-p$). We take the mean-field limit of $Z^N$, leading to a…

Probability · Mathematics 2021-10-14 Peter Pfaffelhuber , Stefan Rotter , Jakob Stiefel

In the present work, we introduce a general class of mean-field interacting nonlinear Hawkes processes modelling the reciprocal interactions between two neuronal populations, one excitatory and one inhibitory. The model incorporates two…

Probability · Mathematics 2021-05-25 Céline Duval , Eric Luçon , Christophe Pouzat

We consider spatially extended systems of interacting nonlinear Hawkes processes modeling large systems of neurons placed in Rd and study the associated mean field limits. As the total number of neurons tends to infinity, we prove that the…

Probability · Mathematics 2018-02-19 Julien Chevallier , A Duarte , E Löcherbach , G Ost

Hawkes processes are a class of simple point processes whose intensity depends on the past history, and is in general non-Markovian. Limit theorems for Hawkes processes in various asymptotic regimes have been studied in the literature. In…

Probability · Mathematics 2026-05-25 Fuqing Gao , Lingjiong Zhu

We generalize multivariate Hawkes processes mainly by including a dependence with respect to the age of the process, i.e. the delay since the last point. Within this class, we investigate the limit behaviour, when n goes to infinity, of a…

Probability · Mathematics 2017-03-16 Julien Chevallier

In this paper, we establish general scaling limits for nearly unstable Hawkes processes in a mean-field regime by extending the method introduced by Jaisson and Rosenbaum. Under a mild asymptotic criticality condition on the self-exciting…

Probability · Mathematics 2025-01-22 Grégoire Szymanski , Wei Xu

We consider a sequence of systems of Hawkes processes having mean field interactions in a diffusive regime. The stochastic intensity of each process is a solution of a stochastic differential equation driven by N independent Poisson random…

Probability · Mathematics 2020-11-24 Xavier Erny , Eva Löcherbach , Dasha Loukianova

The Hawkes process is a counting process that has self- and mutually-exciting features with many applications in various fields. In recent years, there have been many interests in the mean-field results of the Hawkes process and its…

Probability · Mathematics 2023-08-01 Fuqing Gao , Yunshi Gao , Lingjiong Zhu

We investigate the asymptotic behaviour of networks of interacting non-linear Hawkes processes modeling a homogeneous population of neurons in the large population limit. In particular, we prove a functional central limit theorem for the…

Probability · Mathematics 2021-07-06 Sophie Heesen , Wilhelm Stannat

We consider a population of $N$ individuals, of which we observe the number of actions as time evolves. For each couple of individuals $(i,j)$, $j$ may or not influence $i$, which we model by i.i.d. Bernoulli$(p)$-random variables, for some…

Statistics Theory · Mathematics 2016-01-28 Sylvain Delattre , Nicolas Fournier

We consider the problem of learning the network of mutual excitations (i.e., the dependency graph) in a non-stationary, multivariate Hawkes process. We consider a general setting where baseline rates at each node are time-varying and delay…

Statistics Theory · Mathematics 2026-01-21 Elchanan Mossel , Anirudh Sridhar

We propose a fast and efficient estimation method that is able to accurately recover the parameters of a d-dimensional Hawkes point-process from a set of observations. We exploit a mean-field approximation that is valid when the…

Machine Learning · Computer Science 2016-04-20 Emmanuel Bacry , Stéphane Gaïffas , Iacopo Mastromatteo , Jean-François Muzy

We consider a population of $N$ interacting neurons, represented by a multivariate Hawkes process: the firing rate of each neuron depends on the history of the connected neurons. Contrary to the mean-field framework where the interaction…

Probability · Mathematics 2022-02-24 Zoé Agathe-Nerine

Hawkes process is a simple point process that is self-exciting and has clustering effect. The intensity of this point process depends on its entire past history. It has wide applications in finance, neuroscience, social networks,…

Probability · Mathematics 2018-10-02 Xuefeng Gao , Lingjiong Zhu

We generalise the construction of multivariate Hawkes processes to a possibly infinite network of counting processes on a directed graph $\mathbb G$. The process is constructed as the solution to a system of Poisson driven stochastic…

Probability · Mathematics 2014-03-25 Sylvain Delattre , Nicolas Fournier , Marc Hoffmann

The Hawkes self-excited point process provides an efficient representation of the bursty intermittent dynamics of many physical, biological, geological and economic systems. By expressing the probability for the next event per unit time…

Statistical Mechanics · Physics 2020-09-23 Kiyoshi Kanazawa , Didier Sornette

A univariate Hawkes process is a simple point process that is self-exciting and has clustering effect. The intensity of this point process is given by the sum of a baseline intensity and another term that depends on the entire past history…

Probability · Mathematics 2018-10-04 Xuefeng Gao , Lingjiong Zhu

We investigate the nonparametric estimation problem of the density $\pi$, representing the stationary distribution of a two-dimensional system $\left(Z_t\right)_{t \in[0, T]}=\left(X_t, \lambda_t\right)_{t \in[0, T]}$. In this system, $X$…

Statistics Theory · Mathematics 2025-10-01 Chiara Amorino , Charlotte Dion-Blanc , Arnaud Gloter , Sarah Lemler

We introduce a multivariate Hawkes process with constraints on its conditional density. It is a multivariate point process with conditional intensity similar to that of a multivariate Hawkes process but certain events are forbidden with…

Applications · Statistics 2014-02-14 Ban Zheng , François Roueff , Frédéric Abergel

We consider a system of $N$ Hawkes processes and observe the actions of a subpopulation of size $K \le N$ up to time $t$, where $K$ is large. The influence relationships between each pair of individuals are modeled by i.i.d.Bernoulli($p$)…

Probability · Mathematics 2026-01-06 Chenguang Liu , Liping Xu , An Zhang
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