La partenza per MaxEnt 2009

Just to let this indefinable perfume of Italy linger for a few more posts, but there is no objective reason to switch to Italian… I am actually off to Oxford, Mississippi, at the MaxEnt 2009 meeting, which is the 29th workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering. Despite the strong connections with my research interests, I have never attended one of those conferences and this sounds exciting. Especially given my talk there on computational methods, which covers in particular nested sampling with the critical views summarised in this post. This promises for interesting exchanges, since the inventor of nested sampling, John Skilling, is one of the founding fathers of the maximum entropy community.

NS1

This will also give me the opportunity to go over the new revision of the paper before sending it back to Biometrika. The reviews were so lukewarm that I was ready to pack up and go. Fortunately, Nicolas Chopin overrode my depressive tendencies and launched into the revision! All I have to do in the coming days is thus to compile once again the seven pages of the Biometrika style manual to make sure we comply with every item of it. (The editorial requests of Biometrika go beyond most other journals’, even PNAS, which is a pain when writing a paper, because the time spent of complying with the stylistic restrictions will be wasted if the paper is rejected!, but which is also most enjoyable at the reader’s level.)

Oxford is the home town of William Faulkner and. as such, enjoys a literary atmosphere (whatever that means) with several genuine bookstores, including Square Books. Given that I have never been in the South (Florida being a separate geographical entity!), this is also an interesting opportunity. Even though I am not looking forward the hot, clammy, humid weather (humidity is currently 78% at 11pm…). And considering that MaxEnt 2003 was in Jackson Hole, Wyoming…

One Response to “La partenza per MaxEnt 2009”

  1. Hi Christian,

    It will be good to see you there, and I look forward to hearing the debates around Nested Sampling. I think it has some strengths and some weaknesses, and in my opinion the main weakness is that it presupposes you can do something that you actually can’t (generate the new point independently from the constrained distribution).

    I have a wish-list of features I’d like to see a general Bayesian computation algorithm to have, maybe you can develop one that satisfies my criteria. :)

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