The application visualization system: a computational environment for scientific visualization. - Craig Upson; Thomas A. Faulhaber Jr.; David Kamins; David H. Laidlaw; David Schlegel; Jefrey Vroom; Robert F. Gurwitz; Andries van Dam (IEEE Computer Graphics and Applications, 1989)

Celeste: Variational inference for a generative model of astronomical images. - Jeffrey Regier; Andrew C. Miller; Jon McAuliffe; Ryan P. Adams; Matthew D. Hoffman; Dustin Lang; David Schlegel; Prabhat (ICML, 2015)

A Gaussian Process Model of Quasar Spectral Energy Distributions. - Andrew C. Miller; Albert Wu; Jeffrey Regier; Jon McAuliffe; Dustin Lang; Prabhat; David Schlegel; Ryan P. Adams (NIPS, 2015)

Learning an Astronomical Catalog of the Visible Universe through Scalable Bayesian Inference. - Jeffrey Regier; Kiran Pamnany; Ryan Giordano; Rollin C. Thomas; David Schlegel; Jon McAuliffe; Prabhat (CoRR, 2016)

Cataloging the Visible Universe Through Bayesian Inference at Petascale. - Jeffrey Regier; Kiran Pamnany; Keno Fischer; Andreas Noack 001; Maximilian Lam; Jarrett Revels; Steve Howard; Ryan Giordano; David Schlegel; Jon McAuliffe; Rollin C. Thomas; Prabhat (IPDPS, 2018)

Approximate Inference for Constructing Astronomical Catalogs from Images. - Jeffrey Regier; Andrew C. Miller; David Schlegel; Ryan P. Adams; Jon D. McAuliffe; Prabhat (CoRR, 2018)

Cataloging the visible universe through Bayesian inference in Julia at petascale. - Jeffrey Regier; Keno Fischer; Kiran Pamnany; Andreas Noack 001; Jarrett Revels; Maximilian Lam; Steve Howard; Ryan Giordano; David Schlegel; Jon McAuliffe; Rollin C. Thomas; Prabhat (J. Parallel Distributed Comput., 2019)

A Semi-Supervised Learning Method for the Identification of Bad Exposures in Large Imaging Surveys. - Yufeng Luo; Adam D. Myers; Alex Drlica-Wagner; Dario Dematties; Salma Borchani; Frank Valdes; Arjun Dey; David Schlegel; Rongpu Zhou; DESI Legacy Imaging Surveys Team (CoRR, 2025)