Testing Unfaithful Gaussian Graphical Models

NeurIPS 2014 De Wen SohSekhar C. Tatikonda

The global Markov property for Gaussian graphical models ensures graph separation implies conditional independence. Specifically if a node set $S$ graph separates nodes $u$ and $v$ then $X_u$ is conditionally independent of $X_v$ given $X_S$... (read more)

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