Jeffrey Regier

36 papers A* 8A 2Journal 24Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Globally Convergent Variational Inference. CoRR Declan McNamara, Jackson Loper, Jeffrey Regier
2025	J	`jnl`	Neural Posterior Estimation for Cataloging Astronomical Images from the Legacy Survey of Space and Time. CoRR Yicun Duan, Xinyue Li, Camille Avestruz, Jeffrey Regier
2025	J	`jnl`	Neural Posterior Estimation for Cataloging Astronomical Images with Spatially Varying Backgrounds and Point Spread Functions. CoRR Aakash Patel, Tianqing Zhang, Camille Avestruz, Jeffrey Regier, LSST Dark Energy Science Collaboration
2025	J	`jnl`	Neural Posterior Estimation with Autoregressive Tiling for Detecting Objects in Astronomical Images. CoRR Jeffrey Regier
2024	A*	`conf`	Globally Convergent Variational Inference. NeurIPS Declan McNamara, Jackson Loper, Jeffrey Regier
2024	A	`conf`	Sequential Monte Carlo for Inclusive KL Minimization in Amortized Variational Inference. AISTATS Declan McNamara, Jackson Loper, Jeffrey Regier
2024	J	`jnl`	Sequential Monte Carlo for Inclusive KL Minimization in Amortized Variational Inference. CoRR Declan McNamara, Jackson Loper, Jeffrey Regier
2024	A*	`conf`	Variational Inference with Coverage Guarantees in Simulation-Based Inference. ICML Yash P. Patel, Declan McNamara, Jackson Loper, Jeffrey Regier, Ambuj Tewari
2023	J	`jnl`	Diffusion Models for Probabilistic Deconvolution of Galaxy Images. CoRR Zhiwei Xue, Yuhang Li, Yash P. Patel, Jeffrey Regier
2023	J	`jnl`	Variational Inference for Deblending Crowded Starfields. J. Mach. Learn. Res. Runjing Liu, Jon D. McAuliffe, Jeffrey Regier, LSST Dark Energy Science Collaboration
2023	J	`jnl`	Variational Inference with Coverage Guarantees. CoRR Yash P. Patel, Declan McNamara, Jackson Loper, Jeffrey Regier, Ambuj Tewari
2022	J	`jnl`	Dynamic Survival Transformers for Causal Inference with Electronic Health Records. CoRR Prayag Chatha, Yixin Wang, Zhenke Wu, Jeffrey Regier
2022	A*	`conf`	Normalizing Flows for Knockoff-free Controlled Feature Selection. NeurIPS Derek Hansen, Brian Manzo, Jeffrey Regier
2021	J	`jnl`	Normalizing Flows for Knockoff-free Controlled Feature Selection. CoRR Derek Hansen, Brian Manzo, Jeffrey Regier
2021	J	`jnl`	Variational Inference for Deblending Crowded Starfields. CoRR Runjing Liu, Jon D. McAuliffe, Jeffrey Regier
2020	A*	`conf`	Decision-Making with Auto-Encoding Variational Bayes. NeurIPS Romain Lopez, Pierre Boyeau, Nir Yosef, Michael I. Jordan, Jeffrey Regier
2020	J	`jnl`	Decision-Making with Auto-Encoding Variational Bayes. CoRR Romain Lopez, Pierre Boyeau, Nir Yosef, Michael I. Jordan, Jeffrey Regier
2020	J	`jnl`	Flows Succeed Where GANs Fail: Lessons from Low-Dimensional Data. CoRR Tianci Liu, Jeffrey Regier
2019	J	`jnl`	A joint model of unpaired data from scRNA-seq and spatial transcriptomics for imputing missing gene expression measurements. CoRR Romain Lopez, Achille Nazaret, Maxime Langevin, Jules Samaran, Jeffrey Regier, Michael I. Jordan, Nir Yosef
2019	J	`jnl`	Cataloging the visible universe through Bayesian inference in Julia at petascale. J. Parallel Distributed Comput. Jeffrey Regier, Keno Fischer, Kiran Pamnany, Andreas Noack, Jarrett Revels, Maximilian Lam, Steve Howard, Ryan Giordano, David Schlegel, Jon McAuliffe, Rollin C. Thomas, Prabhat
2019	A*	`conf`	Rao-Blackwellized Stochastic Gradients for Discrete Distributions. ICML Runjing Liu, Jeffrey Regier, Nilesh Tripuraneni, Michael I. Jordan, Jon D. McAuliffe
2018	J	`jnl`	A Deep Generative Model for Semi-Supervised Classification with Noisy Labels. CoRR Maxime Langevin, Edouard Mehlman, Jeffrey Regier, Romain Lopez, Michael I. Jordan, Nir Yosef
2018	J	`jnl`	Approximate Inference for Constructing Astronomical Catalogs from Images. CoRR Jeffrey Regier, Andrew C. Miller, David Schlegel, Ryan P. Adams, Jon D. McAuliffe, Prabhat
2018	A	`conf`	Cataloging the Visible Universe Through Bayesian Inference at Petascale. IPDPS Jeffrey Regier, Kiran Pamnany, Keno Fischer, Andreas Noack, Maximilian Lam, Jarrett Revels, Steve Howard, Ryan Giordano, David Schlegel, Jon McAuliffe, Rollin C. Thomas, Prabhat
2018	J	`jnl`	Cataloging the Visible Universe through Bayesian Inference at Petascale. CoRR Jeffrey Regier, Kiran Pamnany, Keno Fischer, Andreas Noack, Maximilian Lam, Jarrett Revels, Steve Howard, Ryan Giordano, David Schlegel, Jon McAuliffe, Rollin C. Thomas, Prabhat
2018	A*	`conf`	Information Constraints on Auto-Encoding Variational Bayes. NeurIPS Romain Lopez, Jeffrey Regier, Michael I. Jordan, Nir Yosef
2018	J	`jnl`	Information Constraints on Auto-Encoding Variational Bayes. CoRR Romain Lopez, Jeffrey Regier, Nir Yosef, Michael I. Jordan
2018	J	`jnl`	Rao-Blackwellized Stochastic Gradients for Discrete Distributions. CoRR Runjing Liu, Jeffrey Regier, Nilesh Tripuraneni, Michael I. Jordan, Jon McAuliffe
2018	A*	`conf`	Stochastic Cubic Regularization for Fast Nonconvex Optimization. NeurIPS Nilesh Tripuraneni, Mitchell Stern, Chi Jin, Jeffrey Regier, Michael I. Jordan
2017	J	`jnl`	A deep generative model for gene expression profiles from single-cell RNA sequencing. CoRR Romain Lopez, Jeffrey Regier, Michael I. Jordan, Nir Yosef
2017	—	`conf`	Fast Black-box Variational Inference through Stochastic Trust-Region Optimization. NIPS Jeffrey Regier, Michael I. Jordan, Jon McAuliffe
2017	J	`jnl`	Fast Black-box Variational Inference through Stochastic Trust-Region Optimization. CoRR Jeffrey Regier, Michael I. Jordan, Jon McAuliffe
2017	J	`jnl`	Stochastic Cubic Regularization for Fast Nonconvex Optimization. CoRR Nilesh Tripuraneni, Mitchell Stern, Chi Jin, Jeffrey Regier, Michael I. Jordan
2016	J	`jnl`	Learning an Astronomical Catalog of the Visible Universe through Scalable Bayesian Inference. CoRR Jeffrey Regier, Kiran Pamnany, Ryan Giordano, Rollin C. Thomas, David Schlegel, Jon McAuliffe, Prabhat
2015	—	`conf`	A Gaussian Process Model of Quasar Spectral Energy Distributions. NIPS Andrew C. Miller, Albert Wu, Jeffrey Regier, Jon McAuliffe, Dustin Lang, Prabhat, David Schlegel, Ryan P. Adams
2015	A*	`conf`	Celeste: Variational inference for a generative model of astronomical images. ICML Jeffrey Regier, Andrew C. Miller, Jon McAuliffe, Ryan P. Adams, Matthew D. Hoffman, Dustin Lang, David Schlegel, Prabhat