  Continuous-time event sequences play a vital role in real-world domains such
as healthcare, finance, online shopping, social networks, and so on. To model
such data, temporal point processes (TPPs) have emerged as the most natural and
competitive models, making a significant impact in both academic and
application communities. Despite the emergence of many powerful models in
recent years, there hasn't been a central benchmark for these models and future
research endeavors. This lack of standardization impedes researchers and
practitioners from comparing methods and reproducing results, potentially
slowing down progress in this field. In this paper, we present EasyTPP, the
first central repository of research assets (e.g., data, models, evaluation
programs, documentations) in the area of event sequence modeling. Our EasyTPP
makes several unique contributions to this area: a unified interface of using
existing datasets and adding new datasets; a wide range of evaluation programs
that are easy to use and extend as well as facilitate reproducible research;
implementations of popular neural TPPs, together with a rich library of modules
by composing which one could quickly build complex models. All the data and
implementation can be found at
https://github.com/ant-research/EasyTemporalPointProcess. We will actively
maintain this benchmark and welcome contributions from other researchers and
practitioners. Our benchmark will help promote reproducible research in this
field, thus accelerating research progress as well as making more significant
real-world impacts.
