data-driven discovery

Part of CampHogg had lunch with David Sontag (NYU) today; Sontag works on tractable approximations to intractable Bayesian inferences (among other things). In particular, he is interested in making scientific discoveries in data using non-trivial Bayesian models. We spent much of lunch discussing the gap between supervised and unsupervised methods; most important scientific tasks don't fall clearly into one category or the other, and progress in the huge region between them could be immensely useful. I pitched several April-Fools scale projects at Sontag; none have quite stuck yet.

In the afternoon, Christian Ott (Caltech) gave a nice talk about numerical modeling of exploding stars, and the persistent problem that supernova explosions do not reliably happen on the computer. That deep problem has been around for all the time I have been an astrophysicist!

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