Inference in Temporal Models

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Destrezas que aprenderás

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

Reseñas

4.6 (476 calificaciones)

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LC

2 de feb. de 2019

Very great course! A lot of things have been learnt. The lectures, quiz and assignments clear up all key concepts. Especially, assignments are wonderful!

LL

11 de mar. de 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.

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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