Robert B. Gramacy

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 26

Top Topics

Stochastic Simulation

Gaussian Process

Stochastic Process

Top Venues

Stat. Anal. Data Min.

SIAM/ASA J. Uncertain. Quantification

Publications

Nathan Wycoff, John W. Smith, Annie S. Booth, Robert B. Gramacy
Voronoi Candidates for Bayesian Optimization. CoRR (2024)
Christine M. Anderson-Cook, Lu Lu, Robert B. Gramacy, L. Allison Jones-Farmer, Douglas C. Montgomery, William H. Woodall
Publishing an applied statistics paper: Guidance and advice from editors. Qual. Reliab. Eng. Int. 40 (4) (2024)
Annie Sauer, Robert B. Gramacy, David Higdon
Active Learning for Deep Gaussian Process Surrogates. Technometrics 65 (1) (2023)
Ryan B. Christianson, Ryan M. Pollyea, Robert B. Gramacy
Traditional kriging versus modern Gaussian processes for large-scale mining data. Stat. Anal. Data Min. 16 (5) (2023)
Annie Sauer, Andrew Cooper, Robert B. Gramacy
Vecchia-Approximated Deep Gaussian Processes for Computer Experiments. J. Comput. Graph. Stat. 32 (3) (2023)
Ryan B. Christianson, Robert B. Gramacy
Robust expected improvement for Bayesian optimization. CoRR (2023)
Chiwoo Park, Robert Waelder, Bonggwon Kang, Benji Maruyama, Soondo Hong, Robert B. Gramacy
Active Learning of Piecewise Gaussian Process Surrogates. CoRR (2023)
Nathan Wycoff, Mickaël Binois, Robert B. Gramacy
Sensitivity Prewarping for Local Surrogate Modeling. Technometrics 64 (4) (2022)
Jiangeng Huang, Robert B. Gramacy
Multi-Output Calibration of a Honeycomb Seal via On-site Surrogates. Technometrics 64 (4) (2022)
D. Austin Cole, Robert B. Gramacy, Mike Ludkovski
Large-scale local surrogate modeling of stochastic simulation experiments. Comput. Stat. Data Anal. 174 (2022)
Robert B. Gramacy, Annie Sauer, Nathan Wycoff
Triangulation candidates for Bayesian optimization. NeurIPS (2022)
Nathan Wycoff, Mickaël Binois, Robert B. Gramacy
Sensitivity Prewarping for Local Surrogate Modeling. CoRR (2021)
Robert B. Gramacy, Annie Sauer, Nathan Wycoff
Triangulation candidates for Bayesian optimization. CoRR (2021)
D. Austin Cole, Ryan B. Christianson, Robert B. Gramacy
Locally induced Gaussian processes for large-scale simulation experiments. Stat. Comput. 31 (3) (2021)
Adam M. Edwards, Robert B. Gramacy
Precision aggregated local models. Stat. Anal. Data Min. 14 (6) (2021)
Mickaël Binois, Robert B. Gramacy
hetGP: Heteroskedastic Gaussian Process Modeling and Sequential Design in R. J. Stat. Softw. 98 (1) (2021)
Boya Zhang, D. Austin Cole, Robert B. Gramacy
Distance-Distributed Design for Gaussian Process Surrogates. Technometrics 63 (1) (2021)
Matthias Chung, Mickaël Binois, Robert B. Gramacy, Johnathan M. Bardsley, David J. Moquin, Amanda P. Smith, Amber M. Smith
Parameter and Uncertainty Estimation for Dynamical Systems Using Surrogate Stochastic Processes. SIAM J. Sci. Comput. 41 (4) (2019)
Furong Sun, Robert B. Gramacy, Benjamin Haaland, Siyuan Lu, Youngdeok Hwang
Synthesizing simulation and field data of solar irradiance. Stat. Anal. Data Min. 12 (4) (2019)
Mickaël Binois, Jiangeng Huang, Robert B. Gramacy, Mike Ludkovski
Replication or Exploration? Sequential Design for Stochastic Simulation Experiments. Technometrics 61 (1) (2019)
Furong Sun, Robert B. Gramacy, Benjamin Haaland, Earl Lawrence, Andrew Walker
Emulating Satellite Drag from Large Simulation Experiments. SIAM/ASA J. Uncertain. Quantification 7 (2) (2019)
Timothy Graves, Robert B. Gramacy, Nicholas Watkins, Christian Franzke
A Brief History of Long Memory: Hurst, Mandelbrot and the Road to ARFIMA, 1951-1980. Entropy 19 (9) (2017)
Victor Picheny, Robert B. Gramacy, Stefan M. Wild, Sébastien Le Digabel
Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian. NIPS (2016)
Robert B. Gramacy, Genetha A. Gray, Sébastien Le Digabel, Herbert K. H. Lee, Pritam Ranjan, Garth N. Wells, Stefan M. Wild
Modeling an Augmented Lagrangian for Blackbox Constrained Optimization. Technometrics 58 (1) (2016)
Robert B. Gramacy, Benjamin Haaland
Speeding Up Neighborhood Search in Local Gaussian Process Prediction. Technometrics 58 (3) (2016)
Robert B. Gramacy, Genetha A. Gray, Sébastien Le Digabel, Herbert K. H. Lee, Pritam Ranjan, Garth N. Wells, Stefan M. Wild
Rejoinder. Technometrics 58 (1) (2016)
Robert B. Gramacy, Michael Ludkovski
Sequential Design for Optimal Stopping Problems. SIAM J. Financial Math. 6 (1) (2015)
Ricardo Bezerra de Andrade e Silva, Robert B. Gramacy
Gaussian Process Structural Equation Models with Latent Variables. CoRR (2014)
Robert B. Gramacy, Jarad Niemi, Robin Weiss
Massively Parallel Approximate Gaussian Process Regression. SIAM/ASA J. Uncertain. Quantification 2 (1) (2014)
Christoforos Anagnostopoulos, Robert B. Gramacy
Information-Theoretic Data Discarding for Dynamic Trees on Data Streams. Entropy 15 (12) (2013)
Yuao Hu, Robert B. Gramacy, Heng Lian
Bayesian quantile regression for single-index models. Stat. Comput. 23 (4) (2013)
Robert B. Gramacy
Comment: On Advances in Expected Improvement. Technometrics 55 (1) (2013)
Robert B. Gramacy, Jarad Niemi, Robin Weiss
Massively parallel approximate Gaussian process regression. CoRR (2013)
Prasanna Balaprakash, Karl Rupp, Azamat Mametjanov, Robert B. Gramacy, Paul D. Hovland, Stefan M. Wild
Empirical performance modeling of GPU kernels using active learning. PARCO (2013)
Prasanna Balaprakash, Robert B. Gramacy, Stefan M. Wild
Active-learning-based surrogate models for empirical performance tuning. CLUSTER (2013)
Hugh A. Chipman, Edward I. George, Robert B. Gramacy, Robert E. McCulloch
Bayesian treed response surface models. WIREs Data Mining Knowl. Discov. 3 (4) (2013)
Robert B. Gramacy, Heng Lian
Gaussian Process Single-Index Models as Emulators for Computer Experiments. Technometrics 54 (1) (2012)
Robert B. Gramacy, Herbert K. H. Lee
Cases for the nugget in modeling computer experiments. Stat. Comput. 22 (3) (2012)
Tamara Broderick, Robert B. Gramacy
Classification and Categorical Inputs with Treed Gaussian Process Models. J. Classif. 28 (2) (2011)
Ricardo Bezerra de Andrade e Silva, Robert B. Gramacy
Gaussian Process Structural Equation Models with Latent Variables. UAI (2010)
Robert B. Gramacy, Richard Samworth, Ruth King
Importance tempering. Stat. Comput. 20 (1) (2010)
Robert B. Gramacy, Herbert K. H. Lee
Adaptive Design and Analysis of Supercomputer Experiments. Technometrics 51 (2) (2009)
Ricardo Bezerra de Andrade e Silva, Robert B. Gramacy
MCMC Methods for Bayesian Mixtures of Copulas. AISTATS (2009)
Robert B. Gramacy, Herbert K. H. Lee
Gaussian processes and limiting linear models. Comput. Stat. Data Anal. 53 (1) (2008)
Robert B. Gramacy, Herbert K. H. Lee, William G. Macready
Parameter space exploration with Gaussian process trees. ICML (2004)
Ismail Ari, Ahmed Amer, Robert B. Gramacy, Ethan L. Miller, Scott A. Brandt, Darrell D. E. Long
ACME: Adaptive Caching Using Multiple Experts. WDAS (2002)
Robert B. Gramacy, Manfred K. Warmuth, Scott A. Brandt, Ismail Ari
Adaptive Caching by Refetching. NIPS (2002)