Interpretable Transformer Hawkes Processes: Unveiling Complex Interactions in Social Networks-Reference-Cited by-同舟云学术

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Interpretable Transformer Hawkes Processes: Unveiling Complex Interactions in Social Networks

Published:2024-08-24 Issue: Volume:1 Page:2200-2211
ISSN:
Container-title:Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Meng Zizhuo¹^ORCID,Wan Ke²^ORCID,Huang Yadong³^ORCID,Li Zhidong¹^ORCID,Wang Yang¹^ORCID,Zhou Feng⁴^ORCID

Affiliation:

1. The University of Technology Sydney, Sydney, Australia

2. University of Illinois at Urbana-Champaign, Urbana, IL, USA

3. Zhoushan Academy of Marine Data Science, Zhoushan, China

4. Center for Applied Statistics and School of Statistics, Renmin University of China & Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beijing, China

Funder

NSFC Project

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3637528.3671720

Reference40 articles.

1. Change detection in non-stationary Hawkes processes through sequential testing

2. Pierre Brémaud and Laurent Massoulié. 1996. Stability of nonlinear Hawkes processes. The Annals of Probability (1996), 1563--1588.

3. Daryl J Daley and David Vere-Jones. 2003. An introduction to the theory of point processes. Vol. I. Probability and its Applications.

4. Daryl J Daley and David Vere-Jones. 2007. An Introduction to the Theory of Point Processes: Volume II: General Theory and Structure. Springer Science & Business Media.

5. Zheng Dong, Xiuyuan Cheng, and Yao Xie. 2022. Spatio-temporal point processes with deep non-stationary kernels. arXiv preprint arXiv:2211.11179 (2022).

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