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Picture for Jeffrey Regier

Jeffrey Regier

for the LSST Dark Energy Science Collaboration

Variational Inference for Deblending Crowded Starfields


Feb 04, 2021
Runjing Liu, Jon D. McAuliffe, Jeffrey Regier

* 37 pages; 20 figures; 3 tables. Submitted to the Journal of the American Statistical Association 

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Flows Succeed Where GANs Fail: Lessons from Low-Dimensional Data


Jun 17, 2020
Tianci Liu, Jeffrey Regier


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Decision-Making with Auto-Encoding Variational Bayes


Feb 17, 2020
Romain Lopez, Pierre Boyeau, Nir Yosef, Michael I. Jordan, Jeffrey Regier


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A joint model of unpaired data from scRNA-seq and spatial transcriptomics for imputing missing gene expression measurements


May 06, 2019
Romain Lopez, Achille Nazaret, Maxime Langevin, Jules Samaran, Jeffrey Regier, Michael I. Jordan, Nir Yosef

* submitted to the 2019 ICML Workshop on Computational Biology 

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Information Constraints on Auto-Encoding Variational Bayes


Oct 15, 2018
Romain Lopez, Jeffrey Regier, Michael I. Jordan, Nir Yosef

* Advances in Neural Information Processing Systems 2018 

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Approximate Inference for Constructing Astronomical Catalogs from Images


Oct 12, 2018
Jeffrey Regier, Andrew C. Miller, David Schlegel, Ryan P. Adams, Jon D. McAuliffe, Prabhat

* major revision for AoAS 

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Rao-Blackwellized Stochastic Gradients for Discrete Distributions


Oct 10, 2018
Runjing Liu, Jeffrey Regier, Nilesh Tripuraneni, Michael I. Jordan, Jon McAuliffe

* 7 pages, 6 figures; submitted to AISTATS 2019 

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A Deep Generative Model for Semi-Supervised Classification with Noisy Labels


Sep 16, 2018
Maxime Langevin, Edouard Mehlman, Jeffrey Regier, Romain Lopez, Michael I. Jordan, Nir Yosef

* accepted to BayLearn 2018 

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A deep generative model for gene expression profiles from single-cell RNA sequencing


Jan 16, 2018
Romain Lopez, Jeffrey Regier, Michael Cole, Michael Jordan, Nir Yosef

* BayLearn2017, NIPS workshop MLCB 2017 

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Stochastic Cubic Regularization for Fast Nonconvex Optimization


Dec 05, 2017
Nilesh Tripuraneni, Mitchell Stern, Chi Jin, Jeffrey Regier, Michael I. Jordan

* The first two authors contributed equally 

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Fast Black-box Variational Inference through Stochastic Trust-Region Optimization


Nov 05, 2017
Jeffrey Regier, Michael I. Jordan, Jon McAuliffe

* NIPS 2017 camera-ready 

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A deep generative model for single-cell RNA sequencing with application to detecting differentially expressed genes


Oct 17, 2017
Romain Lopez, Jeffrey Regier, Michael Cole, Michael Jordan, Nir Yosef

* Updated a previous submission instead. See arXiv:1709.02082 

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Learning an Astronomical Catalog of the Visible Universe through Scalable Bayesian Inference


Nov 10, 2016
Jeffrey Regier, Kiran Pamnany, Ryan Giordano, Rollin Thomas, David Schlegel, Jon McAuliffe, Prabhat

* submitting to IPDPS'17 

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Celeste: Variational inference for a generative model of astronomical images


Jun 03, 2015
Jeffrey Regier, Andrew Miller, Jon McAuliffe, Ryan Adams, Matt Hoffman, Dustin Lang, David Schlegel, Prabhat

* in the Proceedings of the 32nd International Conference on Machine Learning (2015) 

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