# Hawkes Processes Modeling, Inference and Control: An Overview

arXiv: https://arxiv.org/abs/2011.13073 · HTML: https://mlsanity.com/paper/2011.13073/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Nov 2020.

## Built on by (most cited first, 3 of 3)

- [Bayes Risk Consistency of Nonparametric Classification Rules for Spike Trains Data](https://mlsanity.com/paper/2308.04796/) (2023)
- [Hiding Backdoors within Event Sequence Data via Poisoning Attacks](https://mlsanity.com/paper/2308.10201/) (2023)
- [Patient Trajectory Prediction: Integrating Clinical Notes with Transformers](https://mlsanity.com/paper/2502.18009/) (2025)

## Abstract (arXiv)

Hawkes Processes are a type of point process which models self-excitement among time events. It has been used in a myriad of applications, ranging from finance and earthquakes to crime rates and social network activity analysis.Recently, a surge of different tools and algorithms have showed their way up to top-tier Machine Learning conferences. This work aims to give a broad view of the recent advances on the Hawkes Processes modeling and inference to a newcomer to the field.