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ORCIDRyan Giordano
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- affiliation: University of California, Berkeley, Department of Statistics
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2020 – today
- 2024
[j3]Ryan Giordano, Martin Ingram, Tamara Broderick:
Black Box Variational Inference with a Deterministic Objective: Faster, More Accurate, and Even More Black Box. J. Mach. Learn. Res. 25: 18:1-18:39 (2024)- 2023
- [c4]Renato Berlinghieri, Brian L. Trippe, David R. Burt, Ryan James Giordano, Kaushik Srinivasan
, Tamay M. Özgökmen, Junfei Xia, Tamara Broderick:
Gaussian processes at the Helm(holtz): A more fluid model for ocean currents. ICML 2023: 2113-2163 - [i6]Renato Berlinghieri, Brian L. Trippe, David R. Burt, Ryan Giordano, Kaushik Srinivasan, Tamay M. Özgökmen, Junfei Xia, Tamara Broderick:
Gaussian processes at the Helm(holtz): A more fluid model for ocean currents. CoRR abs/2302.10364 (2023) - [i5]Ryan Giordano, Martin Ingram, Tamara Broderick:
Black Box Variational Inference with a Deterministic Objective: Faster, More Accurate, and Even More Black Box. CoRR abs/2304.05527 (2023)
2010 – 2019
- 2019
- [j2]Jeffrey Regier, Keno Fischer, Kiran Pamnany, Andreas Noack, Jarrett Revels, Maximilian Lam, Steve Howard, Ryan Giordano, David Schlegel, Jon McAuliffe, Rollin C. Thomas, Prabhat:
Cataloging the visible universe through Bayesian inference in Julia at petascale. J. Parallel Distributed Comput. 127: 89-104 (2019) - [c3]Ryan Giordano, William T. Stephenson, Runjing Liu, Michael I. Jordan, Tamara Broderick:
A Swiss Army Infinitesimal Jackknife. AISTATS 2019: 1139-1147 - [i4]Ryan Giordano, Michael I. Jordan, Tamara Broderick:
A Higher-Order Swiss Army Infinitesimal Jackknife. CoRR abs/1907.12116 (2019) - 2018
- [j1]Ryan Giordano, Tamara Broderick, Michael I. Jordan:
Covariances, Robustness, and Variational Bayes. J. Mach. Learn. Res. 19: 51:1-51:49 (2018) - [c2]Jeffrey Regier, Kiran Pamnany, Keno Fischer, Andreas Noack, Maximilian Lam, Jarrett Revels, Steve Howard, Ryan Giordano, David Schlegel, Jon McAuliffe, Rollin C. Thomas, Prabhat:
Cataloging the Visible Universe Through Bayesian Inference at Petascale. IPDPS 2018: 44-53 - [i3]Jeffrey Regier, Kiran Pamnany, Keno Fischer, Andreas Noack, Maximilian Lam, Jarrett Revels, Steve Howard, Ryan Giordano, David Schlegel, Jon McAuliffe, Rollin C. Thomas, Prabhat:
Cataloging the Visible Universe through Bayesian Inference at Petascale. CoRR abs/1801.10277 (2018) - 2016
- [i2]Jeffrey Regier, Kiran Pamnany, Ryan Giordano, Rollin C. Thomas, David Schlegel, Jon McAuliffe, Prabhat:
Learning an Astronomical Catalog of the Visible Universe through Scalable Bayesian Inference. CoRR abs/1611.03404 (2016) - 2015
- [c1]Ryan Giordano, Tamara Broderick, Michael I. Jordan:
Linear Response Methods for Accurate Covariance Estimates from Mean Field Variational Bayes. NIPS 2015: 1441-1449 - 2014
- [i1]Ryan Giordano, Tamara Broderick:
Covariance Matrices for Mean Field Variational Bayes. CoRR abs/1410.6853 (2014)
Coauthor Index
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