Learning Continuous Time Bayesian Networks in Non-stationary Domains

Learning Continuous Time Bayesian Networks in Non-stationary Domains

Simone Villa, Fabio Stella

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
Journal track. Pages 5656-5660. https://doi.org/10.24963/ijcai.2018/804

Non-stationary continuous time Bayesian networks are introduced. They allow the parents set of each node in a continuous time Bayesian network to change over time. Structural learning of nonstationary continuous time Bayesian networks is developed under different knowledge settings. A macroeconomic dataset is used to assess the effectiveness of learning non-stationary continuous time Bayesian networks from real-world data.
Keywords:
Uncertainty in AI: Bayesian Networks
Multidisciplinary Topics and Applications: Finance
Multidisciplinary Topics and Applications: Biology and Medicine