Robert B. Gramacy

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Mickael BinoisInria Sophia Antipolis - MéditerranéeVerified email at inria.fr
Nicholas W WatkinsVisiting Professor, LSEVerified email at lse.ac.uk
Christian L. E. FranzkeCenter for Climate Physics, Institute for Basic Science (IBS)Verified email at pusan.ac.kr
Stefan M. WildArgonne National Laboratory, Mathematics & Computer Science DivisionVerified email at mcs.anl.gov
Furong SunRegeneron PharmaceuticalsVerified email at regeneron.com
Leah R. JohnsonVirginia TechVerified email at vt.edu
Sébastien Le DigabelGERAD and Polytechnique MontréalVerified email at polymtl.ca
Nick PolsonProfessor of Econometrics and Statistics, University of ChicagoVerified email at chicagobooth.edu
Mike LudkovskiProfessor, UC Santa BarbaraVerified email at pstat.ucsb.edu
Ben HaalandUniversity of UtahVerified email at hsc.utah.edu
Jiangeng HuangRoche-GenentechVerified email at gene.com
Finn LindgrenUniversity of EdinburghVerified email at ed.ac.uk
Florian GerberDepartment of Applied Mathematics and Statistics, Colorado School of MinesVerified email at mines.edu
Reinhard FurrerProfessor of Applied Statistics, University of ZurichVerified email at math.uzh.ch
Matthias KatzfussAssociate Professor of Statistics, Texas A&M UniversityVerified email at stat.tamu.edu
Rajarshi GuhaniyogiAssociate Professor of Statistics, UC Santa CruzVerified email at ucsc.edu
Matthew HeatonAssociate Professor, Department of Statistics, Brigham Young UniversityVerified email at stat.byu.edu
Abhirup DattaAssociate Professor, Biostatistics, Bloomberg School of Public Health, Johns Hopkins UniversityVerified email at jhu.edu
Andrew FinleyDepartment of Forestry, Michigan State UniversityVerified email at msu.edu
Andrew Zammit MangionUniversity of WollongongVerified email at uow.edu.au

Robert B. Gramacy

Virginia Tech

Verified email at vt.edu - Homepage

statistics machine learning optimization uncertainty quantification


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Bayesian treed Gaussian process models with an application to computer modeling RB Gramacy, HKH Lee Journal of the American Statistical Association 103 (483), 1119-1130, 2008	723	2008
Local Gaussian process approximation for large computer experiments RB Gramacy, DW Apley Journal of Computational and Graphical Statistics 24 (2), 561-578, 2015	320	2015
A case study competition among methods for analyzing large spatial data MJ Heaton, A Datta, AO Finley, R Furrer, J Guinness, R Guhaniyogi, ... Journal of Agricultural, Biological and Environmental Statistics 24 (3), 398-425, 2019	302*	2019
Cases for the nugget in modeling computer experiments RB Gramacy, HKH Lee Statistics and Computing 22 (3), 713-722, 2012	269	2012
tgp: an R package for Bayesian nonstationary, semiparametric nonlinear regression and design by treed Gaussian process models RB Gramacy Journal of Statistical Software 19, 1-46, 2007	238	2007
Adaptive design and analysis of supercomputer experiments RB Gramacy, HKH Lee Technometrics 51 (2), 130-145, 2009	236	2009
Categorical inputs, sensitivity analysis, optimization and importance tempering with tgp version 2, an R package for treed Gaussian process models RB Gramacy, M Taddy Journal of Statistical Software 33, 1-48, 2010	219*	2010
Importance tempering R Gramacy, R Samworth, R King Statistics and Computing 20 (1), 1-7, 2010	218	2010
Surrogates: Gaussian process modeling, design, and optimization for the applied sciences RB Gramacy Chapman and Hall/CRC, 2020	203	2020
Practical heteroscedastic Gaussian process modeling for large simulation experiments M Binois, RB Gramacy, M Ludkovski Journal of Computational and Graphical Statistics 27 (4), 808-821, 2018	153	2018
Optimization under unknown constraints RB Gramacy, HKH Lee Bayesian Statistics 9 9, 229, 2011	153*	2011
A brief history of long memory: Hurst, Mandelbrot and the road to ARFIMA, 1951–1980 T Graves, R Gramacy, N Watkins, C Franzke Entropy 19 (9), 437, 2017	135*	2017
ACME: Adaptive Caching Using Multiple Experts I Ari, A Amer, RB Gramacy, EL Miller, SA Brandt, DDE Long WDAS, 143-158, 2002	133	2002
Particle learning of Gaussian process models for sequential design and optimization RB Gramacy, NG Polson Journal of Computational and Graphical Statistics 20 (1), 102-118, 2011	131	2011
Dynamic trees for learning and design MA Taddy, RB Gramacy, NG Polson Journal of the American Statistical Association 106 (493), 109-123, 2011	130	2011
Modeling an augmented Lagrangian for blackbox constrained optimization RB Gramacy, GA Gray, S Le Digabel, HKH Lee, P Ranjan, G Wells, ... Technometrics 58 (1), 1-11, 2016	119	2016
laGP: large-scale spatial modeling via local approximate Gaussian processes in R RB Gramacy Journal of Statistical Software 72, 1-46, 2016	118	2016
Bayesian treed Gaussian process models RB Gramacy University of California, Santa Cruz, 2005	117	2005
An open challenge to advance probabilistic forecasting for dengue epidemics MA Johansson, KM Apfeldorf, S Dobson, J Devita, AL Buczak, B Baugher, ... Proceedings of the National Academy of Sciences 116 (48), 24268-24274, 2019	109	2019
Geometry: mesh generation and surface tesselation R Grasman, RB Gramacy R package version 0.1-4. URL http://cran. r-project. org/web/packages/geometry, 2008	97*	2008

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