Graph Theory in Stereo: When Causality Meets Correlation in Categorical Space
Graph Theory in Stereo: When Causality Meets Correlation in Categorical Space Graphs look clean until they start carrying probability. A Bayesian network says: these variables have directed relationships; each node comes with a conditional distribution. A Markov network says: these variables interact symmetrically; each clique carries a potential. Both are old tools. Both are useful. Both are also a little too easy to treat as pictures with numbers attached, which is how software systems eventually grow a nice coat of ambiguity. ...