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Human behavior drives a range of complex social, urban, and economic systems, yet understanding its structure and dynamics at the individual level remains an open question. From credit card transactions to communications data, human…

Social and Information Networks · Computer Science 2020-05-15 Sharon Xu , Steven Morse , Marta C. González

Hawkes processes are a class of point processes that have the ability to model the self- and mutual-exciting phenomena. Although the classic Hawkes processes cover a wide range of applications, their expressive ability is limited due to…

Machine Learning · Computer Science 2021-06-10 Feng Zhou , Quyu Kong , Yixuan Zhang , Cheng Feng , Jun Zhu

Sequences of events including infectious disease outbreaks, social network activities, and crimes are ubiquitous and the data on such events carry essential information about the underlying diffusion processes between communities (e.g.,…

Social and Information Networks · Computer Science 2021-06-08 Maya Okawa , Tomoharu Iwata , Yusuke Tanaka , Hiroyuki Toda , Takeshi Kurashima , Hisashi Kashima

Existing spatio-temporal Hawkes process models typically rely on either parametric or semiparametric assumptions, limiting the model's ability to capture complex endogenous and exogenous event dynamics. We propose a fully Bayesian…

Methodology · Statistics 2026-03-31 Wenqing Liu , Xenia Miscouridou , Déborah Sulem

The Hawkes process is a widely used model in many areas, such as finance, seismology, neuroscience, epidemiology, and social sciences. Estimation of the Hawkes process from continuous observations of a sample path is relatively…

Methodology · Statistics 2024-01-23 Feng Chen , Jeffrey Kwan , Tom Stindl

Earthquake occurrence is notoriously difficult to predict. While some aspects of their spatiotemporal statistics can be relatively well captured by point-process models, very little is known regarding the magnitude of future events, and it…

Geophysics · Physics 2026-04-29 Neri Berman , Oleg Zlydenko , Oren Gilon , Yossi Matias , Yohai Bar-Sinai

Recently proposed encoder-decoder structures for modeling Hawkes processes use transformer-inspired architectures, which encode the history of events via embeddings and self-attention mechanisms. These models deliver better prediction and…

Machine Learning · Computer Science 2022-02-07 Yamac Alican Isik , Connor Davis , Paidamoyo Chapfuwa , Ricardo Henao

We investigate the spatial distribution of aftershocks and we find that aftershock linear density exhibits a maximum, that depends on the mainshock magnitude, followed by a power law decay. The exponent controlling the asymptotic decay and…

Geophysics · Physics 2009-07-17 E. Lippiello , L. de Arcangelis , C. Godano

Modeling seismic activity rates and clustering plays an important role in studies of induced seismicity associated with mining and other resource extraction operations. This is critical for understanding the physical and statistical…

Multivariate Hawkes Processes (MHPs) are a class of point processes that can account for complex temporal dynamics among event sequences. In this work, we study the accuracy and computational efficiency of three classes of algorithms which,…

Computation · Statistics 2025-02-24 Alex Ziyu Jiang , Abel Rodríguez

We introduce and establish the main properties of QHawkes ("Quadratic" Hawkes) models. QHawkes models generalize the Hawkes price models introduced in E. Bacry et al. (2014), by allowing all feedback effects in the jump intensity that are…

Trading and Market Microstructure · Quantitative Finance 2015-09-28 Pierre Blanc , Jonathan Donier , Jean-Philippe Bouchaud

A key difficulty that arises from real event data is imprecision in the recording of event time-stamps. In many cases, retaining event times with a high precision is expensive due to the sheer volume of activity. Combined with practical…

Methodology · Statistics 2020-01-22 Leigh Shlomovich , Edward Cohen , Niall Adams , Lekha Patel

The field of study of complex systems holds that the dynamics of complex systems are founded on universal principles that may used to describe a great variety of scientific and technological approaches of different types of natural,…

Over the past few decades, the Hawkes process has become a popular framework for modeling temporal events thanks to its flexibility to capture different dependency structures. The objective of this work is to model call sequences emitted by…

Methodology · Statistics 2025-07-29 Anna Bonnet , Stéphane Robin

In this paper we study the frequentist properties of Bayesian approaches in linear high dimensional Hawkes processes in a sparse regime where the number of interaction functions acting on each component of the Hawkes process is much smaller…

Statistics Theory · Mathematics 2025-10-29 Judith Rousseau , Vincent Rivoirard , Déborah Sulem

In this paper, we propose an extension of the Hawkes process by incorporating a kernel based on the tempered Mittag-Leffler distribution. This is the generalization of the work presented in [10]. We derive analytical results for the…

Probability · Mathematics 2024-08-22 Neha Gupta , Aditya Maheshwari

We propose a novel approach to marked Hawkes kernel inference which we name the moment-based neural Hawkes estimation method. Hawkes processes are fully characterized by their first and second order statistics through a Fredholm integral…

Trading and Market Microstructure · Quantitative Finance 2026-02-02 Timothée Fabre , Ioane Muni Toke

We present an analytical solution and numerical tests of the epidemic-type aftershock (ETAS) model for aftershocks, which describes foreshocks, aftershocks and mainshocks on the same footing. The occurrence rate of aftershocks triggered by…

Statistical Mechanics · Physics 2015-06-24 A. Helmstetter , D. Sornette

Hawkes processes are a popular framework to model the occurrence of sequential events, i.e., occurrence dynamics, in several fields such as social diffusion. In real-world scenarios, the inter-arrival time among events is irregular.…

Machine Learning · Computer Science 2023-05-19 Minju Jo , Seungji Kook , Noseong Park

The productivity of a magnitude $m$ event can be characterized in term of triggered events of magnitude above $m-\Delta$: it is the number of direct "descendants" $\nu_\Delta$ and the number of all "descendants" $V_\Delta$. There is…

Geophysics · Physics 2022-09-05 George Molchan , Elisa Varini , Antonella Peresan