Neural Temporal Point Processes: A Review

Understand

Temporal point processes (TPP) are probabilistic generative models for continuous-time event sequences.

• Neural TPPs combine the fundamental ideas from point process literature with deep learning approaches, thus enabling construction of flexible and efficient models.
• The topic of neural TPPs has attracted significant attention in the recent years, leading to the development of numerous new architectures and applications for this class of models.
• In this review paper we aim to consolidate the existing body of knowledge on neural TPPs.