Maximum a Posteriori Estimation by Search in Probabilistic Programs

26 Apr 2015David TolpinFrank Wood

We introduce an approximate search algorithm for fast maximum a posteriori probability estimation in probabilistic programs, which we call Bayesian ascent Monte Carlo (BaMC). Probabilistic programs represent probabilistic models with varying number of mutually dependent finite, countable, and continuous random variables... (read more)

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