Integrating expert’s knowledge constraint of time dependent exposures in structure learning for Bayesian networks

作者：

Highlights：

• Introduction of an approach for learning dynamic Bayesian network (DBN).

• Use of a priori expert knowledge as hard constraint.

• Different time modelling assumptions tested.

• Better recovery of true graphs.

摘要

•Introduction of an approach for learning dynamic Bayesian network (DBN).•Use of a priori expert knowledge as hard constraint.•Different time modelling assumptions tested.•Better recovery of true graphs.

论文关键词：Dynamic Bayesian network,Graphical structure learning,VAR model,Time dependent exposure

论文评审过程：Received 22 August 2018, Revised 25 March 2020, Accepted 2 May 2020, Available online 2 June 2020, Version of Record 9 July 2020.

论文官网地址：https://doi.org/10.1016/j.artmed.2020.101874