| Multi-output separable Gaussian process: Towards an efficient, fully Bayesian paradigm for uncertainty quantification I Bilionis, N Zabaras, BA Konomi, G Lin Journal of Computational Physics 241, 212-239, 2013 | 194 | 2013 |
| Adaptive Bayesian nonstationary modeling for large spatial datasets using covariance approximations BA Konomi, H Sang, BK Mallick Journal of Computational and Graphical Statistics 23 (3), 802-829, 2014 | 57 | 2014 |
| Bayesian treed multivariate gaussian process with adaptive design: Application to a carbon capture unit B Konomi, G Karagiannis, A Sarkar, X Sun, G Lin Technometrics 56 (2), 145-158, 2014 | 35 | 2014 |
| A Bayesian mixed shrinkage prior procedure for spatial–stochastic basis selection and evaluation of gPC expansions: Applications to elliptic SPDEs G Karagiannis, BA Konomi, G Lin Journal of Computational Physics 284, 528-546, 2015 | 23 | 2015 |
| Full scale multi-output Gaussian process emulator with nonseparable auto-covariance functions B Zhang, BA Konomi, H Sang, G Karagiannis, G Lin Journal of computational physics 300, 623-642, 2015 | 17 | 2015 |
| Bayesian object classification of gold nanoparticles BA Konomi, SS Dhavala, JZ Huang, S Kundu, D Huitink, H Liang, Y Ding, ... | 16 | 2013 |
| Multifidelity Computer Model Emulation with High-Dimensional Output: An Application to Storm Surge P Ma, G Karagiannis, BA Konomi, TG Asher, GR Toro, AT Cox Journal of the Royal Statistical Society: Series C 71 (4), 861-883, 2022 | 14 | 2022 |
| Bayesian Treed Calibration: an application to carbon capture with AX sorbent BA Konomi, G Karagiannis, K Lai, G Lin Journal of the American Statistical Association 112 (517), 37-53, 2017 | 14 | 2017 |
| Computer model emulation with high-dimensional functional output in large-scale observing system uncertainty experiments P Ma, A Mondal, BA Konomi, J Hobbs, JJ Song, EL Kang Technometrics 64 (1), 65-79, 2022 | 13 | 2022 |
| Uncertainty quantification techniques for sensor calibration monitoring in nuclear power plants P Ramuhalli, G Lin, SL Crawford, BA Konomi, JB Coble, B Shumaker, ... Pacific Northwest National Lab.(PNNL), Richland, WA (United States), 2014 | 13 | 2014 |
| On the Bayesian calibration of expensive computer models with input dependent parameters G Karagiannis, BA Konomi, G Lin Spatial Statistics 34, 100258, 2019 | 11 | 2019 |
| Male mastodon landscape use changed with maturation (late Pleistocene, North America) JH Miller, DC Fisher, BE Crowley, R Secord, BA Konomi Proceedings of the National Academy of Sciences 119 (25), e2118329119, 2022 | 9 | 2022 |
| Bayesian analysis of multifidelity computer models with local features and nonnested experimental designs: application to the WRF model BA Konomi, G Karagiannis Technometrics 63 (4), 510-522, 2021 | 9 | 2021 |
| An additive approximate Gaussian process model for large spatio‐temporal data P Ma, BA Konomi, EL Kang Environmetrics, e2569, 2019 | 8 | 2019 |
| Parallel and interacting stochastic approximation annealing algorithms for global optimisation G Karagiannis, BA Konomi, G Lin, F Liang Statistics and Computing 27, 927-945, 2017 | 7 | 2017 |
| Ice model calibration using semicontinuous spatial data W Chang, BA Konomi, G Karagiannis, Y Guan, M Haran The Annals of Applied Statistics 16 (3), 1937-1961, 2022 | 5 | 2022 |
| Hierarchical Bayesian nearest neighbor co-kriging Gaussian process models; an application to intersatellite calibration S Cheng, BA Konomi, JL Matthews, G Karagiannis, EL Kang Spatial Statistics 44, 100516, 2021 | 5 | 2021 |
| Computationally efficient nonstationary nearest‐neighbor Gaussian process models using data‐driven techniques BA Konomi, AA Hanandeh, P Ma, EL Kang Environmetrics, e2571, 2019 | 5 | 2019 |
| On the Bayesian treed multivariate Gaussian process with linear model of coregionalization B Konomi, G Karagiannis, G Lin Journal of Statistical Planning and Inference 157, 1-15, 2015 | 4 | 2015 |
| Uncertainty quantification using the nearest neighbor gaussian process H Shi, EL Kang, BA Konomi, K Vemaganti, S Madireddy New Advances in Statistics and Data Science, 89-107, 2017 | 3 | 2017 |
Guang LinProfessor of Mathematics, Mechanical Engineering, Statistics, Purdue UniversityBestätigte E-Mail-Adresse bei purdue.edu
