Inference in Temporal Models

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Destrezas que aprenderás

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

Reseñas

4.6 (445 calificaciones)
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    22.02%
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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.

De la lección
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.

Impartido por:

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    Daphne Koller

    Professor

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