At the suggestion of Rix (MPIA), Eilers (MPIA), Rix, and I applied Eilers's and my linear model for parallax prediction to the RR Lyrae sample from PanSTARRS and Gaia DR2 today. It worked beautifully, delivering an error-convolved scatter of less than 7 percent, and an error-deconvolved intrinsic scatter of something more like 5 percent in distance. That's exciting! Our features are magnitudes, period, and light-curve shape parameters. Eilers was able to do this all in under an hour, because it was a plug-in replacement for the model we built for upper-red-giant-branch stars. This is another confirmation that on sufficiently small parts of the color–magnitude diagram, linear models can do a great job of predicting stellar properties, especially absolute magnitude or distance. Deep learning be damned!
Aside from this, most of my research time today (and this weekend) was spent writing. Trying to submit the red-giant paper before I depart Germany.