Graphical Models: D-Separation

$$ \newcommand{\bigci}{\perp\mkern-10mu\perp} $$ This article is a brief overview of conditional independence in graphical models, and the related d-separation. Let us begin with a definition. For three random variables $X$, $Y$ and $Z$, we say $X$ is conditionally independent of $Y$ given $Z$ iff $$ p(X, Y | Z) = p(X | Z) p(Y | Z). $$ We can use a shorthand notation $$ X \bigci Y | Z $$

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