Robert B. Gramacy

According to our database, Robert B. Gramacy authored at least 43 papers between 2002 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Publishing an applied statistics paper: Guidance and advice from editors.

Christine M. Anderson-Cook, Lu Lu, Robert B. Gramacy, L. Allison Jones-Farmer, Douglas C. Montgomery, William H. Woodall

Qual. Reliab. Eng. Int., June, 2024

Voronoi Candidates for Bayesian Optimization.

Nathan Wycoff, John W. Smith, Annie S. Booth, Robert B. Gramacy

CoRR, 2024

2023

Traditional kriging versus modern Gaussian processes for large-scale mining data.

Ryan B. Christianson, Ryan M. Pollyea, Robert B. Gramacy

Stat. Anal. Data Min., October, 2023

Active Learning for Deep Gaussian Process Surrogates.

Annie Sauer, Robert B. Gramacy, David Higdon

Technometrics, January, 2023

Vecchia-Approximated Deep Gaussian Processes for Computer Experiments.

Annie Sauer, Andrew Cooper, Robert B. Gramacy

J. Comput. Graph. Stat., 2023

Robust expected improvement for Bayesian optimization.

Ryan B. Christianson, Robert B. Gramacy

CoRR, 2023

Active Learning of Piecewise Gaussian Process Surrogates.

Chiwoo Park, Robert Waelder, Bonggwon Kang, Benji Maruyama, Soondo Hong, Robert B. Gramacy

CoRR, 2023

2022

Sensitivity Prewarping for Local Surrogate Modeling.

Nathan Wycoff, Mickaël Binois, Robert B. Gramacy

Technometrics, 2022

Multi-Output Calibration of a Honeycomb Seal via On-site Surrogates.

Jiangeng Huang, Robert B. Gramacy

Technometrics, 2022

Large-scale local surrogate modeling of stochastic simulation experiments.

D. Austin Cole, Robert B. Gramacy, Mike Ludkovski

Comput. Stat. Data Anal., 2022

Triangulation candidates for Bayesian optimization.

Robert B. Gramacy, Annie Sauer, Nathan Wycoff

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Distance-Distributed Design for Gaussian Process Surrogates.

Boya Zhang, D. Austin Cole, Robert B. Gramacy

Technometrics, 2021

Precision aggregated local models.

Adam M. Edwards, Robert B. Gramacy

Stat. Anal. Data Min., 2021

Locally induced Gaussian processes for large-scale simulation experiments.

D. Austin Cole, Ryan B. Christianson, Robert B. Gramacy

Stat. Comput., 2021

hetGP: Heteroskedastic Gaussian Process Modeling and Sequential Design in R.

Mickaël Binois, Robert B. Gramacy

J. Stat. Softw., 2021

2019

Replication or Exploration? Sequential Design for Stochastic Simulation Experiments.

Mickaël Binois, Jiangeng Huang, Robert B. Gramacy, Mike Ludkovski

Technometrics, 2019

Parameter and Uncertainty Estimation for Dynamical Systems Using Surrogate Stochastic Processes.

Matthias Chung, Mickaël Binois, Robert B. Gramacy, Johnathan M. Bardsley, David J. Moquin, Amanda P. Smith, Amber M. Smith

SIAM J. Sci. Comput., 2019

Synthesizing simulation and field data of solar irradiance.

Furong Sun, Robert B. Gramacy, Benjamin Haaland, Siyuan Lu, Youngdeok Hwang

Stat. Anal. Data Min., 2019

Emulating Satellite Drag from Large Simulation Experiments.

Furong Sun, Robert B. Gramacy, Benjamin Haaland, Earl Lawrence, Andrew Walker

SIAM/ASA J. Uncertain. Quantification, 2019

2017

A Brief History of Long Memory: Hurst, Mandelbrot and the Road to ARFIMA, 1951-1980.

Timothy Graves, Robert B. Gramacy, Nicholas W. Watkins, Christian Franzke

Entropy, 2017

2016

Speeding Up Neighborhood Search in Local Gaussian Process Prediction.

Robert B. Gramacy, Benjamin Haaland

Technometrics, 2016

Rejoinder.

Robert B. Gramacy, Genetha A. Gray, Sébastien Le Digabel, Herbert K. H. Lee, Pritam Ranjan, Garth N. Wells, Stefan M. Wild

Technometrics, 2016

Modeling an Augmented Lagrangian for Blackbox Constrained Optimization.

Robert B. Gramacy, Genetha A. Gray, Sébastien Le Digabel, Herbert K. H. Lee, Pritam Ranjan, Garth N. Wells, Stefan M. Wild

Technometrics, 2016

Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian.

Victor Picheny, Robert B. Gramacy, Stefan M. Wild, Sébastien Le Digabel

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Sequential Design for Optimal Stopping Problems.

Robert B. Gramacy, Michael Ludkovski

SIAM J. Financial Math., 2015

2014

Massively Parallel Approximate Gaussian Process Regression.

Robert B. Gramacy, Jarad Niemi, Robin Weiss

SIAM/ASA J. Uncertain. Quantification, 2014

2013

Bayesian treed response surface models.

Hugh A. Chipman, Edward I. George, Robert B. Gramacy, Robert E. McCulloch

WIREs Data Mining Knowl. Discov., 2013

Comment: On Advances in Expected Improvement.

Robert B. Gramacy

Technometrics, 2013

Bayesian quantile regression for single-index models.

Yuao Hu, Robert B. Gramacy, Heng Lian

Stat. Comput., 2013

Information-Theoretic Data Discarding for Dynamic Trees on Data Streams.

Christoforos Anagnostopoulos, Robert B. Gramacy

Entropy, 2013

Empirical performance modeling of GPU kernels using active learning.

Prasanna Balaprakash, Karl Rupp, Azamat Mametjanov, Robert B. Gramacy, Paul D. Hovland, Stefan M. Wild

Proceedings of the Parallel Computing: Accelerating Computational Science and Engineering (CSE), 2013

Active-learning-based surrogate models for empirical performance tuning.

Prasanna Balaprakash, Robert B. Gramacy, Stefan M. Wild

Proceedings of the 2013 IEEE International Conference on Cluster Computing, 2013

2012

Gaussian Process Single-Index Models as Emulators for Computer Experiments.

Robert B. Gramacy, Heng Lian

Technometrics, 2012

Cases for the nugget in modeling computer experiments.

Robert B. Gramacy, Herbert K. H. Lee

Stat. Comput., 2012

2011

Classification and Categorical Inputs with Treed Gaussian Process Models.

Tamara Broderick, Robert B. Gramacy

J. Classif., 2011

2010

Importance tempering.

Robert B. Gramacy, Richard Samworth, Ruth King

Stat. Comput., 2010

Gaussian Process Structural Equation Models with Latent Variables.

Ricardo Bezerra de Andrade e Silva, Robert B. Gramacy

Proceedings of the UAI 2010, 2010

2009

Adaptive Design and Analysis of Supercomputer Experiments.

Robert B. Gramacy, Herbert K. H. Lee

Technometrics, 2009

MCMC Methods for Bayesian Mixtures of Copulas.

Ricardo Bezerra de Andrade e Silva, Robert B. Gramacy

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

2008

Gaussian processes and limiting linear models.

Robert B. Gramacy, Herbert K. H. Lee

Comput. Stat. Data Anal., 2008

2004

Parameter space exploration with Gaussian process trees.

Robert B. Gramacy, Herbert K. H. Lee, William G. Macready

Proceedings of the Machine Learning, 2004

2002

ACME: Adaptive Caching Using Multiple Experts.

Ismail Ari, Ahmed Amer, Robert B. Gramacy, Ethan L. Miller, Scott A. Brandt, Darrell D. E. Long

Proceedings of the Distributed Data & Structures 4, 2002

Adaptive Caching by Refetching.

Robert B. Gramacy, Manfred K. Warmuth, Scott A. Brandt, Ismail Ari

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002