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Lecture 12: Approximating Probability Distributions (II): Monte Carlo Methods (I): Importance Sampling, Rejection Sampling, Gibbs Sampling, Metropolis Method
This video was recorded at Course on Information Theory, Pattern Recognition, and Neural Networks. A series of sixteen lectures covering the core of the book "Information Theory, Inference, and Learning Algorithms (Cambridge University Press, 2003)" which can be bought at Amazon, and is available free online. A subset of these lectures used to constitute a Part III Physics course at the University of Cambridge. The high-resolution videos and all other course material can be downloaded from the Cambridge course website.
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This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States
