Various hacking sessions happened in undisclosed locations in Heidelberg this weekend. The most productive moment was that in which—in debugging a think-o about how we combine independent samplings in The Joker—Adrian Price-Whelan (Princeton) and I found a very efficient way to make our samplings adapt to the information in the data (likelihood). That is, we used a predictive adaptation to iteratively expand the number of prior samples we use to an appropriate size for our desired posterior output. (Reminder: The Joker is a rejection sampler.) This ended up speeding up our big parallel set of samplings by a factor of 8-ish!

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