  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.
