KANJDP: Interpretable Temporal Point Process Modeling with Kolmogorov–Arnold Representation

Accurate modeling of event sequences is valuable in domains like electronic health records, financial risk management, and social networks. Random time intervals in these sequences contain key dynamic information, and temporal point processes (TPPs) are widely used to analyze event triggering mechan...

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Bibliographic Details

Published in:	Mathematics
Main Authors:	Ziwei Wu, Guangyin Jin, Xueqiang Gu, Chao Wang
Format:	Article
Language:	English
Published:	MDPI AG 2025-08-01
Subjects:	temporal point processes Kolmogorov–Arnold networks jump-diffusion SDEs event prediction
Online Access:	https://www.mdpi.com/2227-7390/13/17/2754