Articles with public access mandates - Matt PlumleeLearn more
Not available anywhere: 4
Building Accurate Emulators for Stochastic Simulations via Quantile Kriging
M Plumlee, R Tuo
Technometrics 56 (4), 466-473, 2014
Mandates: National Natural Science Foundation of China
Lifted Brownian kriging models
M Plumlee, DW Apley
Technometrics 59 (2), 165-177, 2017
Mandates: US National Science Foundation, US Department of Defense
Learning stochastic model discrepancy
M Plumlee, H Lam
2016 Winter Simulation Conference (WSC), 413-424, 2016
Mandates: US National Science Foundation
Latent variable Gaussian process models: A rank‐based analysis and an alternative approach
S Tao, DW Apley, M Plumlee, W Chen
International Journal for Numerical Methods in Engineering 122 (15), 4007-4026, 2021
Mandates: US National Science Foundation, US Department of Energy
Available somewhere: 23
Bayesian calibration of inexact computer models
M Plumlee
Journal of the American Statistical Association 112 (519), 1274-1285, 2017
Mandates: US National Science Foundation
Get on the BAND wagon: a Bayesian framework for quantifying model uncertainties in nuclear dynamics
DR Phillips, RJ Furnstahl, U Heinz, T Maiti, W Nazarewicz, FM Nunes, ...
Journal of Physics G: Nuclear and Particle Physics 48 (7), 072001, 2021
Mandates: US National Science Foundation, US Department of Energy
Calibrating functional parameters in the ion channel models of cardiac cells
M Plumlee, VR Joseph, H Yang
Journal of the American Statistical Association 111 (514), 500-509, 2016
Mandates: US National Science Foundation
Towards precise and accurate calculations of neutrinoless double-beta decay
V Cirigliano, Z Davoudi, J Engel, R Furnstahl, G Hagen, U Heinz, ...
Journal of Physics G: Nuclear and Particle Physics, 2022
Mandates: US National Science Foundation, US Department of Energy
Orthogonal Gaussian process models
M Plumlee, VR Joseph
Statistica Sinica 28 (2), 601-619, 2018
Mandates: US National Science Foundation, US Department of Energy
Scalable adaptive batch sampling in simulation-based design with heteroscedastic noise
A van Beek, UF Ghumman, J Munshi, S Tao, TY Chien, ...
Journal of Mechanical Design 143 (3), 031709, 2021
Mandates: US National Science Foundation
Computer model calibration with confidence and consistency
M Plumlee
Journal of the Royal Statistical Society: Series B 81 (3), 519-545, 2019
Mandates: US National Science Foundation
High-fidelity hurricane surge forecasting using emulation and sequential experiments
M Plumlee, TG Asher, W Chang, MV Bilskie
Mandates: US National Science Foundation
Uncertainty quantification in breakup reactions
Ö Sürer, FM Nunes, M Plumlee, SM Wild
Physical Review C 106 (2), 024607, 2022
Mandates: US National Science Foundation, US Department of Energy
Integration of normative decision-making and batch sampling for global metamodeling
A Van Beek, S Tao, M Plumlee, DW Apley, W Chen
Journal of Mechanical Design 142 (3), 031114, 2020
Mandates: US National Science Foundation, US Department of Defense
Multiresolution functional anova for large-scale, many-input computer experiments
CL Sung, W Wang, M Plumlee, B Haaland
Journal of the American Statistical Association 115 (530), 908-919, 2020
Mandates: US National Science Foundation
Plausible screening using functional properties for simulations with large solution spaces
DJ Eckman, M Plumlee, BL Nelson
Operations Research 70 (6), 3473-3489, 2022
Mandates: US National Science Foundation
Revisiting subset selection
DJ Eckman, M Plumlee, BL Nelson
2020 Winter Simulation Conference (WSC), 2972-2983, 2020
Mandates: US National Science Foundation
Composite grid designs for adaptive computer experiments with fast inference
M Plumlee, CB Erickson, BE Ankenman, E Lawrence
Biometrika 108 (3), 749-755, 2021
Mandates: US National Science Foundation
Improving prediction from stochastic simulation via model discrepancy learning
H Lam, X Zhang, M Plumlee
2017 Winter Simulation Conference (WSC), 1808-1819, 2017
Mandates: US National Science Foundation
A classification method for ranking and selection with covariates
G Keslin, BL Nelson, M Plumlee, BK Pagnoncelli, H Rahimian
2022 Winter Simulation Conference (WSC), 1-12, 2022
Mandates: US National Science Foundation
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