I gave the first of three workshop-like seminars at NYU this week. This one was on reconstructing dynamical models from kinematic measurements in the limits that the potential is integrable and the angles are mixed (the system has evolved for a very long time without resonances).
Bovy handed me a new version of his document on building the underlying, deconvolved distribution which, when given errors, generates the data in a sample, even when the errors are different and large for every point. He tentatively titled it extreme deconvolution
It'll need to be more extreme than that to impress ME!
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