Inference in Temporal Models

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Получаемые навыки

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

Рецензии

4.6 (оценок: 434)
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LL

Mar 12, 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

May 29, 2017

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

Из урока
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.

Преподаватели

  • Daphne Koller

    Daphne Koller

    Professor

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