Markov Chain Monte Carlo

author: Iain Murray, School of Informatics, University of Edinburgh
published: Nov. 2, 2009,   recorded: August 2009,   views: 236073
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Reviews and comments:

Comment1 Kathryn, January 18, 2010 at 12:12 a.m.:

Awesome, thanks to the lecturer and whoever taped it!


Comment2 zsjyhh, November 24, 2010 at 9 a.m.:

Very good!!!


Comment3 ben, November 29, 2010 at 12:02 p.m.:

It is practically impossible to follow since the video is usually not of the whiteboard, but of the lecturer.


Comment4 Nathaniel, April 11, 2011 at 9:31 p.m.:

Very good lecture.

The presenter is clear, organized, and presents some interesting material that is often not found in textbooks.


Comment5 Iain Murray, December 17, 2011 at 3:06 p.m.:

Viewers of this video may want to try the practical exercise that I provided at this summer school. It's available at http://homepages.inf.ed.ac.uk/imurray...


Comment6 Timmy, February 27, 2012 at 2:02 a.m.:

One of the best MCMC tutorials I watched..


Comment7 S, March 26, 2012 at 10:12 a.m.:

This is so great, thank you very much!


Comment8 bg284, April 5, 2012 at 11:12 p.m.:

thanks so much for this tutorial. really demystified MCMC for me, and for the short note you pasted on your website as well.


Comment9 Sandip, May 24, 2012 at 9:43 p.m.:

Is it possible to download this video?


Comment10 Sam, June 29, 2012 at 2:08 p.m.:

Extremely clear tutorial, thanks very much for putting this online Iain.


Comment11 Conor, March 15, 2013 at 8:56 a.m.:

Sandip has already asked- but can I download this video from anywhere? I'm trying to watch it in Malawi... the internet speeds are not the best! (Sandip- it is on YouTube too)


Comment12 Iain Murray, March 18, 2013 at 12:17 p.m.:

Conor: now that the videos are on YouTube, there's lots of ways to download them for personal use. For example the python script http://rg3.github.com/youtube-dl/ and many others. You'll want the pdf of the slides from videolectures.net to go with the video.


Comment13 Andrii Cherniak, December 27, 2013 at 10:52 p.m.:

This is definitely a much better explanation than in Nando de Freitas class. Not that i am saying that Nando does not explain - he does. But this lecture provides a more coherent path in my opinion


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It was a really good intro lecture on MCMC inference.
I'm wondering if someone tried to explain some more advanced features on it like the forward-backward recursion in MCMC inference.
Also, I think providing an actual example of usage of this method on a Bayesian net would also made it more than perfect.


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