Stars and Exoplanets meeting at Flatiron (well on xoom, really) was all about finding stellar streams. Matt Buckley (Rutgers) talked about repurposing to the astrophysical domain machine-learning methods employed in high-energy physics experimental data to find anomalies. Sarah Pearson (Flatiron) talked about building things that evolve from Hough transforms. In both cases we (the audience) argued that the projects should make catalogs of potential streams with low (non-conservative) thresholds: After all, it is better to find low-mass streams plus some junk than it is to miss them: Every stream is potentially uniquely valuable.
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