Barber’s graphical taxonomy of graphical models:
Placeholder for my notes on probabilistic graphical models. In general graphical models are a particular type of way of handling multivariate data based on working out what is conditionally independent of what else.
Thematically, this is scattered across graphical models in inference, learning graphs from data, learning causation from data plus graphs, quantum graphical models because it all looks a bit different with noncommutative probability.
See also diagramming graphical models.
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