Bledar Alexandros Konomi
Bledar Alexandros Konomi
Associate Professor, Department of Mathematical Sciences, University of Cincinnati
Zweryfikowany adres z - Strona główna
Cytowane przez
Cytowane przez
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
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
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
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
Bayesian object classification of gold nanoparticles
BA Konomi, SS Dhavala, JZ Huang, S Kundu, D Huitink, H Liang, Y Ding, ...
The annals of applied Statistics 7 (2), 640-668, 2013
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
Enhanced oil recovery in high salinity high temperature reservoir by chemical flooding
MA Bataweel
Texas A & M University, 2012
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
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
Parallel and interacting stochastic approximation annealing algorithms for global optimisation
G Karagiannis, BA Konomi, G Lin, F Liang
Statistics and Computing 27 (4), 927-945, 2017
On the Bayesian calibration of expensive computer models with input dependent parameters
G Karagiannis, BA Konomi, G Lin
Spatial Statistics 34, 100258, 2019
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
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
Bayesian analysis of multifidelity computer models with local features and non-nested experimental designs: Application to the WRF model
BA Konomi, G Karagiannis
arXiv preprint arXiv:1910.08063, 2019
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
arXiv preprint arXiv:1909.01836, 2019
Computationally efficient nonstationary nearest‐neighbor Gaussian process models using data‐driven techniques
BA Konomi, AA Hanandeh, P Ma, EL Kang
Environmetrics, e2571, 2019
Hierarchical Bayesian Nearest Neighbor Co-Kriging Gaussian Process Models; An Application to Intersatellite Calibration
S Cheng, BA Konomi, JL Matthews, G Karagianis, EL Kang
arXiv preprint arXiv:2004.01341, 2020
Computer Model Emulation with High-Dimensional Functional Output in Large-Scale Observing System Uncertainty Experiments
P Ma, A Mondal, B Konomi, J Hobbs, J Song, E Kang
arXiv preprint arXiv:1911.09274, 2019
Ice Model Calibration Using Semi-continuous Spatial Data
W Chang, BA Konomi, G Karagiannis, Y Guan, M Haran
arXiv preprint arXiv:1907.13554, 2019
An additive approximate Gaussian process model for large spatio‐temporal data
P Ma, BA Konomi, EL Kang
Environmetrics, e2569, 2019
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