MAP estimation is a method of estimating an unknown quantity based on empirical data and prior knowledge. It is related to maximum likelihood estimation, but incorporates a prior distribution to regularize the optimization objective. MAP estimates the mode of the posterior distribution.
Stanford University
Winter 2023
An in-depth study of probabilistic graphical models, combining graph and probability theory. Equips students with the skills to design, implement, and apply these models to solve real-world problems. Discusses Bayesian networks, exact and approximate inference methods, etc.
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