SIAM Review, Volume 65, Issue 2, Page 331-374, May 2023.
Hawkes processes are a type of point process that models self-excitement among time events. They have been used in a myriad of applications, ranging from finance and earthquakes to crime rates and social network activity analysis. Recently, a variety of different tools and algorithms have been presented at top-tier machine learning conferences. This work aims to give a broad view of recent advances in Hawkes process modeling and inference suitable for a newcomer to the field. The parametric, nonparametric, deep learning, and reinforcement learning approaches are broadly discussed, along with the current research challenges for the topic and the real-world limitations of each approach. Illustrative application examples in the modeling of retweeting behavior, earthquake aftershock occurrence, and malaria outbreak modeling are also briefly discussed.

中文翻译：

---

霍克斯过程建模、推理和控制：概述

SIAM Review，第 65 卷，第 2 期，第 331-374 页，2023 年 5 月。
霍克斯过程是一种点过程，它模拟时间事件之间的自激。它们已被用于无数应用，从金融和地震到犯罪率和社交网络活动分析。最近，在顶级机器学习会议上展示了各种不同的工具和算法。这项工作旨在广泛了解霍克斯过程建模和推理的最新进展，适合该领域的新手。广泛讨论了参数、非参数、深度学习和强化学习方法，以及该主题当前的研究挑战和每种方法在现实世界中的局限性。还简要讨论了转发行为建模、地震余震发生和疟疾爆发建模中的说明性应用示例。