Course Notes on Bayesian Netoworks

This node contains one installment of the course notes for MIT's graduate course on the foundations of artificial intelligence. In this course Bayesian networks are taught in one of a three part sequence. First comes hidden Markov models for speech recognition. Then comes Bayesian networks. And finally parsing with stochastic context free grammars and the inside/outside algorithm. These three subjects are all closely related. Both Bayesian networks and stochastic grammars can be viewed as generalizations of hidden Markov models. Presenting the material this way reduced the effort required on the part of the students --- the equations from each of these subjects are directly analogous with one another. Unfortunately, course notes have not been prepared for hidden Markov models or the inside/outside algorithm.

postscript.

David McAllester, February, 1995