Efficient calibration for imperfect computer models R Tuo, CFJ Wu | 168 | 2015 |
A theoretical framework for calibration in computer models: Parametrization, estimation and convergence properties R Tuo, CF Jeff Wu SIAM/ASA Journal on Uncertainty Quantification 4 (1), 767-795, 2016 | 128 | 2016 |
Sequential exploration of complex surfaces using minimum energy designs VR Joseph, T Dasgupta, R Tuo, CFJ Wu Technometrics 57 (1), 64-74, 2015 | 103 | 2015 |
On prediction properties of kriging: Uniform error bounds and robustness W Wang, R Tuo, CF Jeff Wu Journal of the American Statistical Association 115 (530), 920-930, 2020 | 66 | 2020 |
Surrogate modeling of computer experiments with different mesh densities R Tuo, CFJ Wu, D Yu Technometrics 56 (3), 372-380, 2014 | 64 | 2014 |
Building accurate emulators for stochastic simulations via quantile kriging M Plumlee, R Tuo Technometrics 56 (4), 466-473, 2014 | 63 | 2014 |
Differentially private change-point detection R Cummings, S Krehbiel, Y Mei, R Tuo, W Zhang Advances in Neural Information Processing Systems, 10825-10834, 2018 | 44 | 2018 |
Kriging prediction with isotropic Matérn correlations: Robustness and experimental designs R Tuo, W Wang Journal of Machine Learning Research 21 (187), 1-38, 2020 | 36 | 2020 |
Deterministic sampling of expensive posteriors using minimum energy designs VR Joseph, D Wang, L Gu, S Lyu, R Tuo Technometrics, 2019 | 36 | 2019 |
Optimization of multi-fidelity computer experiments via the EQIE criterion X He, R Tuo, CFJ Wu Technometrics 59 (1), 58-68, 2017 | 27 | 2017 |
Principles of inter-amino-acid recognition revealed by binding energies between homogeneous oligopeptides H Du, X Hu, H Duan, L Yu, F Qu, Q Huang, W Zheng, H Xie, J Peng, ... ACS central science 5 (1), 97-108, 2019 | 26 | 2019 |
Adjustments to computer models via projected kernel calibration R Tuo SIAM/ASA Journal on Uncertainty Quantification 7 (2), 553-578, 2019 | 26 | 2019 |
Effective model calibration via sensible variable identification and adjustment with application to composite fuselage simulation Y Wang, X Yue, R Tuo, JH Hunt, J Shi | 25 | 2020 |
On the improved rates of convergence for Matérn-type kernel ridge regression with application to calibration of computer models R Tuo, Y Wang, CF Jeff Wu SIAM/ASA Journal on Uncertainty Quantification 8 (4), 1522-1547, 2020 | 23 | 2020 |
Stochastic convergence of a nonconforming finite element method for the thin plate spline smoother for observational data Z Chen, R Tuo, W Zhang SIAM Journal on Numerical Analysis 56 (2), 635-659, 2018 | 18 | 2018 |
The temporal overfitting problem with applications in wind power curve modeling A Prakash, R Tuo, Y Ding Technometrics 65 (1), 70-82, 2023 | 13 | 2023 |
Prediction based on the Kennedy-O'Hagan calibration model: Asymptotic consistency and other properties R Tuo, CFJ Wu Statistica Sinica, 743-759, 2018 | 13 | 2018 |
Projection pursuit Gaussian process regression G Chen, R Tuo IISE Transactions 55 (9), 901-911, 2023 | 11 | 2023 |
Gaussian process-aided function comparison using noisy scattered data A Prakash, R Tuo, Y Ding Technometrics 64 (1), 92-102, 2022 | 9 | 2022 |
Kernel packet: An exact and scalable algorithm for Gaussian process regression with Matérn correlations H Chen, L Ding, R Tuo Journal of machine learning research 23 (127), 1-32, 2022 | 9 | 2022 |