so much Gaussian processes

The day was all GPs. Markus Bonse (Darmstadt) showed various of us very promising GPLVM results for spectra, where he is constraining part of the (usually unobserved) latent space to look like the label space (like stellar parameters). This fits into the set of things we are doing to enrich the causal structure of existing machine-learning methods, to make them more generalizable and interpretable. In the afternoon, Dan Foreman-Mackey (Flatiron) found substantial issues with GP code written by me and Christina Eilers (MPIA), causing Eilers and I to have to re-derive and re-write some analytic derivatives. That hurt!
Especially since the derivatives involve some hand-coded sparse linear algebra. But right at the end of the day (like with 90 seconds to spare), we got the new derivatives working in the fixed code. Feelings were triumphant.