Variational Inference for Deblending Crowded Starfields

3 code implementations • 4 Feb 2021 • Runjing Liu, Jon D. McAuliffe, Jeffrey Regier

In images collected by astronomical surveys, stars and galaxies often overlap visually.

Bayesian Inference Variational Inference

Approximate Inference for Constructing Astronomical Catalogs from Images

1 code implementation • 28 Feb 2018 • Jeffrey Regier, Andrew C. Miller, David Schlegel, Ryan P. Adams, Jon D. McAuliffe, Prabhat

We present a new, fully generative model for constructing astronomical catalogs from optical telescope image sets.

Variational Inference

Variational Inference: A Review for Statisticians

6 code implementations • 4 Jan 2016 • David M. Blei, Alp Kucukelbir, Jon D. McAuliffe

One of the core problems of modern statistics is to approximate difficult-to-compute probability densities.

Stochastic Optimization Variational Inference

Supervised Topic Models

1 code implementation • NeurIPS 2007 • David M. Blei, Jon D. McAuliffe

We introduce supervised latent Dirichlet allocation (sLDA), a statistical model of labelled documents.

regression Topic Models

A spatially varying two-sample recombinant coalescent, with applications to HIV escape response

no code implementations • NeurIPS 2008 • Alexander Braunstein, Zhi Wei, Shane T. Jensen, Jon D. Mcauliffe

Statistical evolutionary models provide an important mechanism for describing and understanding the escape response of a viral population under a particular therapy.