Adaptive Caching by Refetching. - Robert B. Gramacy; Manfred K. Warmuth; Scott A. Brandt; Ismail Ari (NIPS, 2002)

ACME: Adaptive Caching Using Multiple Experts. - Ismail Ari; Ahmed Amer; Robert B. Gramacy; Ethan L. Miller; Scott A. Brandt; Darrell D. E. Long (WDAS, 2002)

Parameter space exploration with Gaussian process trees. - Robert B. Gramacy; Herbert K. H. Lee; William G. Macready (ICML, 2004)

Gaussian processes and limiting linear models. - Robert B. Gramacy; Herbert K. H. Lee (Comput. Stat. Data Anal., 2008)

MCMC Methods for Bayesian Mixtures of Copulas. - Ricardo Bezerra de Andrade e Silva; Robert B. Gramacy (AISTATS, 2009)

Adaptive Design and Analysis of Supercomputer Experiments. - Robert B. Gramacy; Herbert K. H. Lee (Technometrics, 2009)

Gaussian Process Structural Equation Models with Latent Variables. - Ricardo Bezerra de Andrade e Silva; Robert B. Gramacy (UAI, 2010)

Importance tempering. - Robert B. Gramacy; Richard Samworth; Ruth King (Stat. Comput., 2010)

Classification and Categorical Inputs with Treed Gaussian Process Models. - Tamara Broderick; Robert B. Gramacy (J. Classif., 2011)

Cases for the nugget in modeling computer experiments. - Robert B. Gramacy; Herbert K. H. Lee (Stat. Comput., 2012)

Gaussian Process Single-Index Models as Emulators for Computer Experiments. - Robert B. Gramacy; Heng Lian (Technometrics, 2012)

Active-learning-based surrogate models for empirical performance tuning. - Prasanna Balaprakash; Robert B. Gramacy; Stefan M. Wild (CLUSTER, 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 (PARCO, 2013)

Information-Theoretic Data Discarding for Dynamic Trees on Data Streams. - Christoforos Anagnostopoulos; Robert B. Gramacy (Entropy, 2013)

Bayesian quantile regression for single-index models. - Yuao Hu; Robert B. Gramacy; Heng Lian (Stat. Comput., 2013)

Comment: On Advances in Expected Improvement. - Robert B. Gramacy (Technometrics, 2013)

Bayesian treed response surface models. - Hugh A. Chipman; Edward I. George; Robert B. Gramacy; Robert E. McCulloch (WIREs Data Mining Knowl. Discov., 2013)

Massively Parallel Approximate Gaussian Process Regression. - Robert B. Gramacy; Jarad Niemi; Robin Weiss (SIAM/ASA J. Uncertain. Quantification, 2014)

Sequential Design for Optimal Stopping Problems. - Robert B. Gramacy; Michael Ludkovski (SIAM J. Financial Math., 2015)

Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian. - Victor Picheny; Robert B. Gramacy; Stefan M. Wild; Sébastien Le Digabel (NIPS, 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)

Rejoinder. - Robert B. Gramacy; Genetha A. Gray; Sébastien Le Digabel; Herbert K. H. Lee; Pritam Ranjan; Garth N. Wells; Stefan M. Wild (Technometrics, 2016)

Speeding Up Neighborhood Search in Local Gaussian Process Prediction. - Robert B. Gramacy; Benjamin Haaland (Technometrics, 2016)

A Brief History of Long Memory: Hurst, Mandelbrot and the Road to ARFIMA, 1951-1980. - Timothy Graves; Robert B. Gramacy; Nicholas W. Watkins; Christian L. E. Franzke (Entropy, 2017)

Emulating Satellite Drag from Large Simulation Experiments. - Furong Sun; Robert B. Gramacy; Benjamin Haaland; Earl Lawrence; Andrew Walker (SIAM/ASA J. Uncertain. Quantification, 2019)

Synthesizing simulation and field data of solar irradiance. - Furong Sun; Robert B. Gramacy; Benjamin Haaland; Siyuan Lu 003; Youngdeok Hwang (Stat. Anal. Data Min., 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)

Replication or Exploration? Sequential Design for Stochastic Simulation Experiments. - Mickaël Binois; Jiangeng Huang; Robert B. Gramacy; Mike Ludkovski (Technometrics, 2019)

hetGP: Heteroskedastic Gaussian Process Modeling and Sequential Design in R. - Mickaël Binois; Robert B. Gramacy (J. Stat. Softw., 2021)

Locally induced Gaussian processes for large-scale simulation experiments. - D. Austin Cole; Ryan B. Christianson; Robert B. Gramacy (Stat. Comput., 2021)

Precision aggregated local models. - Adam M. Edwards; Robert B. Gramacy (Stat. Anal. Data Min., 2021)

Distance-Distributed Design for Gaussian Process Surrogates. - Boya Zhang; D. Austin Cole; Robert B. Gramacy (Technometrics, 2021)

Triangulation candidates for Bayesian optimization. - Robert B. Gramacy; Annie Sauer; Nathan Wycoff (NeurIPS, 2022)

Large-scale local surrogate modeling of stochastic simulation experiments. - D. Austin Cole; Robert B. Gramacy; Mike Ludkovski (Comput. Stat. Data Anal., 2022)

Multi-Output Calibration of a Honeycomb Seal via On-site Surrogates. - Jiangeng Huang; Robert B. Gramacy (Technometrics, 2022)

Sensitivity Prewarping for Local Surrogate Modeling. - Nathan Wycoff; Mickaël Binois; Robert B. Gramacy (Technometrics, 2022)

Active Learning of Piecewise Gaussian Process Surrogates. - Chiwoo Park; Robert Waelder; Bonggwon Kang; Benji Maruyama; Soondo Hong; Robert B. Gramacy (CoRR, 2023)

Robust expected improvement for Bayesian optimization. - Ryan B. Christianson; Robert B. Gramacy (CoRR, 2023)

Vecchia-Approximated Deep Gaussian Processes for Computer Experiments. - Annie Sauer; Andrew Cooper; Robert B. Gramacy (J. Comput. Graph. Stat., 2023)

Active Learning for Deep Gaussian Process Surrogates. - Annie Sauer; Robert B. Gramacy; David Higdon (Technometrics, 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., 2023)

Voronoi Candidates for Bayesian Optimization. - Nathan Wycoff; John W. Smith; Annie S. Booth; Robert B. Gramacy (CoRR, 2024)

Publishing an applied statistics paper: Guidance and advice from editors. - Christine M. Anderson-Cook; Lu Lu 007; Robert B. Gramacy; L. Allison Jones-Farmer; Douglas C. Montgomery; William H. Woodall (Qual. Reliab. Eng. Int., 2024)

Augmenting a Simulation Campaign for Hybrid Computer Model and Field Data Experiments. - Scott Koermer; Justin Loda; Aaron Noble; Robert B. Gramacy (Technometrics, 2024)

Modular Jump Gaussian Processes. - Anna R. Flowers; Christopher T. Franck; Mickaël Binois; Chiwoo Park; Robert B. Gramacy (CoRR, 2025)

Monotonic warpings for additive and deep Gaussian processes. - Steven D. Barnett; Lauren J. Beesley; Annie S. Booth; Robert B. Gramacy; Dave Osthus (Stat. Comput., 2025)