Ryan Giordano - RankMe

13 papers A 2Journal 10Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences. J. Mach. Learn. Res. Mikolaj J. Kasprzak, Ryan Giordano, Tamara Broderick
2024	J	`jnl`	Black Box Variational Inference with a Deterministic Objective: Faster, More Accurate, and Even More Black Box. J. Mach. Learn. Res. Ryan Giordano, Martin Ingram, Tamara Broderick
2023	J	`jnl`	Black Box Variational Inference with a Deterministic Objective: Faster, More Accurate, and Even More Black Box. CoRR Ryan Giordano, Martin Ingram, Tamara Broderick
2023	J	`jnl`	Gaussian processes at the Helm(holtz): A more fluid model for ocean currents. CoRR Renato Berlinghieri, Brian L. Trippe, David R. Burt, Ryan Giordano, Kaushik Srinivasan, Tamay M. Özgökmen, Junfei Xia, Tamara Broderick
2019	J	`jnl`	A Higher-Order Swiss Army Infinitesimal Jackknife. CoRR Ryan Giordano, Michael I. Jordan, Tamara Broderick
2019	A	`conf`	A Swiss Army Infinitesimal Jackknife. AISTATS Ryan Giordano, William T. Stephenson, Runjing Liu, Michael I. Jordan, Tamara Broderick
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
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	J	`jnl`	Covariances, Robustness, and Variational Bayes. J. Mach. Learn. Res. Ryan Giordano, Tamara Broderick, 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`	Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes. NIPS Ryan Giordano, Tamara Broderick, Michael I. Jordan
2014	J	`jnl`	Covariance Matrices for Mean Field Variational Bayes. CoRR Ryan Giordano, Tamara Broderick