3.9k citations · 5.7k across the 13 of their papers we have counts for
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cs.DC2016★ 7 cited
Learning an Astronomical Catalog of the Visible Universe through Scalable Bayesian Inference
Jeffrey Regier, Kiran Pamnany, Ryan Giordano +4
Celeste is a procedure for inferring astronomical catalogs that attains state-of-the-art scientific results. To date, Celeste has been scaled to at most hundreds of megabytes of as…
stat.CO2016★ 3.9k cited
Variational Inference: A Review for Statisticians
David M. Blei, Alp Kucukelbir, Jon D. McAuliffe
One of the core problems of modern statistics is to approximate difficult-to-compute probability densities. This problem is especially important in Bayesian statistics, which frame…