Inference in Temporal Models

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Получаемые навыки

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

Рецензии

4.6 (оценок: 474)

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LC

2 февр. 2019 г.

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 мар. 2017 г.

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.

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

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    Daphne Koller

    Professor

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