My day started with a long breakfast conversation with Yann LeCun (NYU) about adversarial methods in deep learning. In these methods, a generator and discriminator are trained simultaneously, and against one another. It is a great method for finding or describing complex density functions in high dimensions, and people in the business have high hopes. In particular, it is crushing in image applications. We discussed the problem that is currently on my mind, which is modeling the color–magnitude diagram of stars in Gaia, using one of these adversarial systems, plus a good noise model for the parallaxes. I would love to do that, and it should be much easier than the image problems, because the data are much lower in dimensionality.
I ran a very amusing session at the Summit, in which we had participants bring figures and we crowd-sourced a reaction, critique, and to-do list for each of them. We looked at a figure from politics from Michael Gill (NYU), making a causal claim about regulations and how meeting minutes are kept, a figure from geophysics from Nicholas Swanson-Hysell (Berkeley) showing the data and a model for polar wander, and a figure from neuroscience from Bijan Pesaran (NYU) showing brain region classifications. The feedback from the group was great and useful and constructive (though not always polite; my apologies!). One theme of our discussion ended up being consistency across figure elements. I feel like this crowd-sourcing session was a model for future sessions; it would even be fun to make this a regular event in some forum in NYC.
There was a lot of non-research today, but in the remainder of my research time, I worked on outline material for our growing paper on Hack Weeks.