Bayesian methodsBayesian / computational
Hierarchical Bayesian Network
A hierarchical Bayesian network is a probabilistic graphical model that organizes variables across multiple levels of abstraction. Higher-level nodes govern the prior distributions of lower-level nodes through hyperparameters, enabling structured sharing of information across groups, contexts, or data subsets while preserving the directed acyclic graph (DAG) representation of conditional dependencies.
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Sources
- Koller, D. & Friedman, N. (2009). Probabilistic Graphical Models: Principles and Techniques. MIT Press. ISBN: 978-0262013192
- Friedman, N., Getoor, L., Koller, D. & Pfeffer, A. (1999). Learning probabilistic relational models. Proceedings of the 16th International Joint Conference on Artificial Intelligence (IJCAI-99), 1300-1307. link ↗