| Bayesian calibration of inexact computer models M Plumlee Journal of the American Statistical Association 112 (519), 1274-1285, 2017 | 143 | 2017 |
| 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 | 82 | 2021 |
| 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 | 61 | 2016 |
| Building Accurate Emulators for Stochastic Simulations via Quantile Kriging M Plumlee, R Tuo Technometrics 56 (4), 466-473, 2014 | 58 | 2014 |
| Fast prediction of deterministic functions using sparse grid experimental designs M Plumlee Journal of the American Statistical Association 109 (508), 1581-1591, 2014 | 39 | 2014 |
| Lifted Brownian kriging models M Plumlee, DW Apley Technometrics 59 (2), 165-177, 2017 | 34 | 2017 |
| Orthogonal Gaussian process models M Plumlee, VR Joseph Statistica Sinica 28 (2), 601-619, 2018 | 31 | 2018 |
| 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 | 27 | 2022 |
| Improvements in storm surge surrogate modeling for synthetic storm parameterization, node condition classification and implementation to small size databases AP Kyprioti, AA Taflanidis, M Plumlee, TG Asher, E Spiller, RA Luettich, ... Natural Hazards 109, 1349-1386, 2021 | 20 | 2021 |
| Computer model calibration with confidence and consistency M Plumlee Journal of the Royal Statistical Society: Series B 81 (3), 519-545, 2019 | 20 | 2019 |
| 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 | 19 | 2021 |
| High-fidelity hurricane surge forecasting using emulation and sequential experiments M Plumlee, TG Asher, W Chang, MV Bilskie | 18 | 2021 |
| Gaussian process modeling for engineered surfaces with applications to Si wafer production M Plumlee, R Jin, V Roshan Joseph, J Shi Stat 2 (1), 159-170, 2013 | 16 | 2013 |
| Uncertainty quantification in breakup reactions Ö Sürer, FM Nunes, M Plumlee, SM Wild Physical Review C 106 (2), 024607, 2022 | 14 | 2022 |
| 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 | 14 | 2020 |
| 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 | 13 | 2020 |
| Revisiting subset selection DJ Eckman, M Plumlee, BL Nelson 2020 Winter Simulation Conference (WSC), 2972-2983, 2020 | 11 | 2020 |
| Bayesian calibration of viscous anisotropic hydrodynamic simulations of heavy-ion collisions D Liyanage, Ö Sürer, M Plumlee, SM Wild, U Heinz Physical Review C 108 (5), 054905, 2023 | 9 | 2023 |
| Plausible screening using functional properties for simulations with large solution spaces DJ Eckman, M Plumlee, BL Nelson Operations Research 70 (6), 3473-3489, 2022 | 9 | 2022 |
| Composite grid designs for adaptive computer experiments with fast inference M Plumlee, CB Erickson, BE Ankenman, E Lawrence Biometrika 108 (3), 749-755, 2021 | 9 | 2021 |
Stefan M. WildBerkeley Lab, Applied Mathematics & Computational Research Division在 lbl.gov 的电子邮件经过验证
