Uncertainty quantification of microclimate variables in building energy models Y Sun, Y Heo, M Tan, H Xie, CF Jeff Wu, G Augenbroe Journal of Building Performance Simulation 7 (1), 17-32, 2014 | 97 | 2014 |
Generalized selective assembly MHY Tan, CFJ Wu IIE Transactions 44 (1), 27-42, 2012 | 41 | 2012 |
Residual distillation: Towards portable deep neural networks without shortcuts G Li, J Zhang, Y Wang, C Liu, M Tan, Y Lin, W Zhang, J Feng, T Zhang Advances in Neural Information Processing Systems 33, 8935-8946, 2020 | 36 | 2020 |
Wind Turbine Modeling with Data-driven Methods and Radially Uniform Designs M Tan, Z Zhang IEEE Transactions on Industrial Informatics, 2016 | 36 | 2016 |
Integrated parameter and tolerance design with computer experiments M Han, MH Yong Tan IIE Transactions 48 (11), 1004-1015, 2016 | 35 | 2016 |
A Bayesian approach for interpreting mean shifts in multivariate quality control MHY Tan, J Shi Technometrics 54 (3), 294-307, 2012 | 33 | 2012 |
Robust design optimization with quadratic loss derived from Gaussian process models MHY Tan, CFJ Wu Technometrics 54 (1), 51-63, 2012 | 31 | 2012 |
Minimax designs for finite design regions MHY Tan Technometrics 55 (3), 346-358, 2013 | 27 | 2013 |
Uncertainty quantification of microclimate variables in building energy simulation Y Sun, Y Heo, H Xie, M Tan, J Wu, G Augenbroe | 27 | 2011 |
Estimation of the Mean and Variance Response Surfaces when the Means and Variances of the Noise Variables are Unknown MHY Tan, SH Ng IIE Transactions 41 (11), 942-956, 2009 | 23 | 2009 |
Gaussian process modeling with boundary information MHY Tan Statistica Sinica, 621-648, 2018 | 20 | 2018 |
Gaussian process modeling of a functional output with information from boundary and initial conditions and analytical approximations MHY Tan Technometrics 60 (2), 209-221, 2018 | 18 | 2018 |
Monotonic quantile regression with Bernstein polynomials for stochastic simulation MHY Tan Technometrics 58 (2), 180-190, 2016 | 15 | 2016 |
Stochastic polynomial interpolation for uncertainty quantification with computer experiments MHY Tan Technometrics 57 (4), 457-467, 2015 | 15 | 2015 |
Robust Parameter Design with Computer Experiments Using Orthonormal Polynomials MHY Tan Technometrics, 2015 | 15 | 2015 |
A Bayesian approach for model selection in fractionated split plot experiments with applications in robust parameter design MHY Tan, CF Jeff Wu Technometrics 55 (3), 359-372, 2013 | 15 | 2013 |
Bayesian optimization of expected quadratic loss for multiresponse computer experiments with internal noise MHY Tan SIAM/ASA Journal on Uncertainty Quantification 8 (3), 891-925, 2020 | 14 | 2020 |
A Gaussian process emulator based approach for Bayesian calibration of a functional input Z Li, MHY Tan Technometrics 64 (3), 299-311, 2022 | 13 | 2022 |
Integrated parameter and tolerance optimization of a centrifugal compressor based on a complex simulator M Han, X Liu, M Huang, MHY Tan Journal of Quality Technology 52 (4), 404-421, 2020 | 13 | 2020 |
Optimal robust and tolerance design for computer experiments with mixture proportion inputs M Han, MHY Tan Quality and Reliability Engineering International 33 (8), 2255-2267, 2017 | 10 | 2017 |