Course Notes
The notes written by students and edited by instructors
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Lecture 13: Approximate Inference: Monte Carlo and Sequential Monte Carlo Methods
Wrapping up variational inference, and overview of Monte Carlo methods.
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Lecture 9: Modeling Networks
Classic network learning algorithms.
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Lecture 6: Learning Partially Observed GM and the EM Algorithm
Introduction to the process of estimating the parameters of graphical models from data using the EM (Baum-Welch) algorithm.
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