46 citations · 80 across the 6 of their papers we have counts for
6 papers
Cataloging the Visible Universe through Bayesian Inference at Petascale
Jeffrey Regier, Kiran Pamnany, Keno Fischer +9
Astronomical catalogs derived from wide-field imaging surveys are an important tool for understanding the Universe. We construct an astronomical catalog from 55 TB of imaging data…
Stochastic Cubic Regularization for Fast Nonconvex Optimization
Nilesh Tripuraneni, Mitchell Stern, Chi Jin +2
This paper proposes a stochastic variant of a classic algorithm---the cubic-regularized Newton method [Nesterov and Polyak 2006]. The proposed algorithm efficiently escapes saddle…
A deep generative model for single-cell RNA sequencing with application to detecting differentially expressed genes
Romain Lopez, Jeffrey Regier, Michael Cole +2
We propose a probabilistic model for interpreting gene expression levels that are observed through single-cell RNA sequencing. In the model, each cell has a low-dimensional latent…
A deep generative model for gene expression profiles from single-cell RNA sequencing
Romain Lopez, Jeffrey Regier, Michael Cole +2
We propose a probabilistic model for interpreting gene expression levels that are observed through single-cell RNA sequencing. In the model, each cell has a low-dimensional latent…
Fast Black-box Variational Inference through Stochastic Trust-Region Optimization
Jeffrey Regier, Michael I. Jordan, Jon McAuliffe
We introduce TrustVI, a fast second-order algorithm for black-box variational inference based on trust-region optimization and the reparameterization trick. At each iteration, Trus…
Celeste: Variational inference for a generative model of astronomical images
Jeffrey Regier, Andrew Miller, Jon McAuliffe +5
We present a new, fully generative model of optical telescope image sets, along with a variational procedure for inference. Each pixel intensity is treated as a Poisson random vari…