In our Gaia DR2 prep meeting, I led a discussion of the likelihood function for Gaia data. I made the standard proposal (Gaussian based on Catalog values). And we discussed a bit when you need to use that (that is, be Bayesian) and when can you just treat the data like truth. As my loyal reader might expect, I advised extreme pragmatism.
In Stars meeting, there was lots of great stuff: Foreman-Mackey (Flatiron) showed us his brand-new Hamiltonian MCMC sampler, which has a super-simple interface, and contains lots of the hacky goodness of STAN. He showed that is blows emcee out of the water for some problems with dozens of parameters. He and Price-Whelan (Princeton) are using this sampler to look for multi-star systems in APOGEE radial-velocity data.
Price-Whelan showed us APOGEE data that show very clear evidence of tidal circularization for (fainter) stars orbiting red-giant stars, and in very good agreement with the theory of this. The situation is easiest to predict, apparently, for giant stars with large convective envelopes. He did both the data analysis and some nice theory with MESA and tidal-circularization differential equations too to support his claims.
Late in the day, Julianne Dalcanton (UW) consulted with Foreman-Mackey and me on a hierarchical model for the dust in M33. She wants to simultaneously learn the dust map and the unreddened color-magnitude diagram as a function of position in the galaxy. That's a great but hard optimization.