Jeffrey Regier

Orcid: 0000-0002-1472-5235

Affiliations:

University of California, Berkeley, Department of Electrical Engineering and Computer Sciences, CA, USA

According to our database¹, Jeffrey Regier authored at least 23 papers between 2015 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2024

Sequential Monte Carlo for Inclusive KL Minimization in Amortized Variational Inference.

[BibT_eX]

[DOI]

Declan McNamara

Jackson Loper

Jeffrey Regier

CoRR, 2024

2023

Variational Inference for Deblending Crowded Starfields.

[BibT_eX]

[DOI]

Runjing Liu

Jon D. McAuliffe

Jeffrey Regier

LSST Dark Energy Science Collaboration

J. Mach. Learn. Res., 2023

Diffusion Models for Probabilistic Deconvolution of Galaxy Images.

[BibT_eX]

[DOI]

CoRR, 2023

Variational Inference with Coverage Guarantees.

[BibT_eX]

[DOI]

CoRR, 2023

2022

Dynamic Survival Transformers for Causal Inference with Electronic Health Records.

[BibT_eX]

[DOI]

CoRR, 2022

Normalizing Flows for Knockoff-free Controlled Feature Selection.

[BibT_eX]

[DOI]

Derek Hansen

Brian Manzo

Jeffrey Regier

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Variational Inference for Deblending Crowded Starfields.

[BibT_eX]

[DOI]

Runjing Liu

Jon D. McAuliffe

Jeffrey Regier

CoRR, 2021

2020

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

[BibT_eX]

[DOI]

Tianci Liu

Jeffrey Regier

CoRR, 2020

Decision-Making with Auto-Encoding Variational Bayes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Cataloging the visible universe through Bayesian inference in Julia at petascale.

[BibT_eX]

[DOI]

J. Parallel Distributed Comput., 2019

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

[BibT_eX]

[DOI]

CoRR, 2019

Rao-Blackwellized Stochastic Gradients for Discrete Distributions.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

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

[BibT_eX]

[DOI]

CoRR, 2018

Approximate Inference for Constructing Astronomical Catalogs from Images.

[BibT_eX]

[DOI]

CoRR, 2018

Stochastic Cubic Regularization for Fast Nonconvex Optimization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Information Constraints on Auto-Encoding Variational Bayes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Cataloging the Visible Universe Through Bayesian Inference at Petascale.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium, 2018

2017

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

[BibT_eX]

[DOI]

CoRR, 2017

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

[BibT_eX]

[DOI]

Jeffrey Regier

Michael I. Jordan

Jon McAuliffe

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

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

[BibT_eX]

[DOI]

CoRR, 2016

2015

Mini-Minimax Uncertainty Quantification for Emulators.

[BibT_eX]

[DOI]

Jeffrey C. Regier

Philip B. Stark

SIAM/ASA J. Uncertain. Quantification, 2015

A Gaussian Process Model of Quasar Spectral Energy Distributions.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Celeste: Variational inference for a generative model of astronomical images.

[BibT_eX]

[DOI]

Proceedings of the 32nd International Conference on Machine Learning, 2015

Jeffrey Regier

Timeline

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