Inference in Temporal Models

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Compétences que vous apprendrez

Inference, Gibbs Sampling, Markov Chain Monte Carlo (MCMC), Belief Propagation

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4.6 (449 évaluations)
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LL
11 mars 2017

Thanks a lot for professor D.K.'s great course for PGM inference part. Really a very good starting point for PGM model and preparation for learning part.

YP
28 mai 2017

I learned pretty much from this course. It answered my quandaries from the representation course, and as well deepened my understanding of PGM.

À partir de la leçon
Inference in Temporal Models
In this brief lesson, we discuss some of the complexities of applying some of the exact or approximate inference algorithms that we learned earlier in this course to dynamic Bayesian networks.

Enseigné par

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    Daphne Koller

    Professor

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