Definition
Graphical models are a means of compactly representing multivariate distributions, allowing for efficient algorithms to be developed when dealing with high-dimensional data. At their core, graphical models make use of the fact that high-dimensional distributions tend to factorize around local interactions, meaning that they can be expressed as a product of low-dimensional terms.
The notation we shall use is defined in Table 1, and some core definitions are presented in Table 2.
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McAuley, J., Caetano, T., Buntine, W.L. (2017). Graphical Models. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_119
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