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Interval-censored data solely records the aggregated counts of events during specific time intervals - such as the number of patients admitted to the hospital or the volume of vehicles passing traffic loop detectors - and not the exact…

Machine Learning · Computer Science 2022-11-29 Marian-Andrei Rizoiu , Alexander Soen , Shidi Li , Pio Calderon , Leanne Dong , Aditya Krishna Menon , Lexing Xie

We provide probabilistic and computational results on Markovian multivariate Hawkes processes and induced population processes. By applying the Markov property, we characterize in closed form a joint transform, bijective to the probability…

Probability · Mathematics 2025-08-08 R. S. Karim , R. J. A. Laeven , M , M. Mandjes

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

Claiming causal inferences in network settings necessitates careful consideration of the often complex dependency between outcomes for actors. Of particular importance are treatment spillover or outcome interference effects. We consider…

Methodology · Statistics 2022-07-18 Duncan A. Clark , Mark S. Handcock

Patient healthcare utilization consists of irregularly time-stamped events, such as outpatient visits, inpatient admissions, and emergency encounters, forming individualized care trajectories. Modeling these trajectories is crucial for…

Machine Learning · Computer Science 2026-04-08 Saumya Pandey , Varun Chandola

In this paper, we develop sample path large deviations for multivariate Hawkes processes with heavy-tailed mutual excitation rates. Our results address a broad class of rare events in Hawkes processes at the sample path level and, via the…

Probability · Mathematics 2025-05-01 Jose Blanchet , Roger J. A. Laeven , Xingyu Wang , Bert Zwart

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

We investigate how the properties of inhomogeneous patterns of activity, appearing in many natural and social phenomena, depend on the temporal resolution used to define individual bursts of activity. To this end, we consider time series of…

Physics and Society · Physics 2021-03-03 Daniele Notarmuzi , Claudio Castellano , Alessandro Flammini , Dario Mazzilli , Filippo Radicchi

We observe the actions of a $K$ sub-sample of $N$ individuals up to time $t$ for some large $K<N$. We model the relationships of individuals by i.i.d. Bernoulli($p$)-random variables, where $p\in (0,1]$ is an unknown parameter. The rate of…

Statistics Theory · Mathematics 2020-04-15 Chenguang Liu

We are interested in the problem of classifying Multivariate Hawkes Processes (MHP) paths coming from several classes. MHP form a versatile family of point processes that models interactions between connected individuals within a network.…

Statistics Theory · Mathematics 2026-03-24 Charlotte Dion-Blanc , Christophe Denis , Laure Sansonnet , Romain Edmond Lacoste

The monitoring of conflict risk in the humanitarian sector is largely based on simple historic averages. The overarching goal of this work is to assess the potential for using a more statistically rigorous approach to monitor the risk of…

Applications · Statistics 2026-02-04 Raiha Browning , Hamish Patten , Judith Rousseau , Kerrie Mengersen

We consider a population of Hawkes processes modeling the activity of $N$ interacting neurons. The neurons are regularly positioned on the segment $[0,1]$, and the connectivity between neurons is given by a random possibly diluted and…

Probability · Mathematics 2022-07-29 Zoé Agathe-Nerine

As a tool for capturing irregular temporal dependencies (rather than resorting to binning temporal observations to construct time series), Hawkes processes with exponential decay have seen widespread adoption across many application…

Machine Learning · Computer Science 2021-04-05 Tiago Santos , Florian Lemmerich , Denis Helic

Hawkes process is a self-exciting point process with clustering effect whose intensity depends on its entire past history. It has wide applications in neuroscience, finance and many other fields. In this paper, we obtain a functional…

Probability · Mathematics 2014-10-16 Lingjiong Zhu

Agentic text-simulation systems write in sequence, with each item becoming possible context for later steps. That makes uncertainty path-dependent: an early ambiguity can affect later outputs. This paper studies this problem with HawkesLLM,…

Computation and Language · Computer Science 2026-05-25 Zewei Deng , Tinghan Ye , Liyan Xie

We introduce and show the existence of a Hawkes self-exciting point process with exponentially-decreasing kernel and where parameters are time-varying. The quantity of interest is defined as the integrated parameter…

Statistical Finance · Quantitative Finance 2017-06-28 Simon Clinet , Yoann Potiron

As a powerful tool of asynchronous event sequence analysis, point processes have been studied for a long time and achieved numerous successes in different fields. Among various point process models, Hawkes process and its variants attract…

Machine Learning · Statistics 2017-08-31 Hongteng Xu , Hongyuan Zha

The Hawkes process is a simple point process with wide applications in finance, social networks, criminology, seismology, and many other fields. The Hawkes process is defined for continuous-time setting. However, data is also recorded in a…

Probability · Mathematics 2021-06-23 Haixu Wang

Ensuring safety in autonomous multi-agent systems during time-critical tasks such as rendezvous is a fundamental challenge, particularly under communication delays and uncertainty in system parameters. In this paper, we develop a…

Systems and Control · Electrical Eng. & Systems 2025-11-27 Vivek Pandey , Nader Motee

Hawkes processes have been shown to be efficient in modeling bursty sequences in a variety of applications, such as finance and social network activity analysis. Traditionally, these models parameterize each process independently and assume…

Machine Learning · Computer Science 2021-02-02 Mengfan Yao , Siqian Zhao , Shaghayegh Sahebi , Reza Feyzi Behnagh