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Simon Mak
Simon Mak
Assistant Professor of Statistical Science, Duke University
在 duke.edu 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Multisystem Bayesian constraints on the transport coefficients of QCD matter
D Everett, W Ke, JF Paquet, G Vujanovic, SA Bass, L Du, C Gale, ...
Physical Review C 103 (5), 054904, 2021
2592021
Phenomenological constraints on the transport properties of QCD matter with data-driven model averaging
D Everett, W Ke, JF Paquet, G Vujanovic, SA Bass, L Du, C Gale, ...
Physical review letters 126 (24), 242301, 2021
1672021
Support points
S Mak, VR Joseph
The Annals of Statistics 46 (6A), 2562-2592, 2018
1532018
Determining the jet transport coefficient from inclusive hadron suppression measurements using Bayesian parameter estimation
S Cao, Y Chen, J Coleman, J Mulligan, PM Jacobs, RA Soltz, A Angerami, ...
Physical Review C 104 (2), 024905, 2021
1242021
An efficient surrogate model for emulation and physics extraction of large eddy simulations
S Mak, CL Sung, X Wang, ST Yeh, YH Chang, VR Joseph, V Yang, ...
Journal of the American Statistical Association 113 (524), 1443-1456, 2017
1172017
Minimax and minimax projection designs using clustering
S Mak, VR Joseph
Journal of Computational and Graphical Statistics 27 (1), 166-178, 2018
722018
Inclusive jet and hadron suppression in a multistage approach
A Kumar, Y Tachibana, C Sirimanna, G Vujanovic, S Cao, A Majumder, ...
Physical Review C 107 (3), 034911, 2023
412023
Energy balancing of covariate distributions
JD Huling, S Mak
Journal of Causal Inference 12 (1), 20220029, 2024
362024
Function-on-function kriging, with applications to three-dimensional printing of aortic tissues
J Chen, S Mak, VR Joseph, C Zhang
Technometrics 63 (3), 384-395, 2021
352021
Common proper orthogonal decomposition-based spatiotemporal emulator for design exploration
ST Yeh, X Wang, CL Sung, S Mak, YH Chang, L Zhang, CFJ Wu, V Yang
AIAA journal 56 (6), 2429-2442, 2018
312018
A hierarchical expected improvement method for Bayesian optimization
Z Chen, S Mak, CF Wu
arXiv preprint arXiv:1911.07285, 2019
27*2019
Efficient emulation of relativistic heavy ion collisions with transfer learning
D Liyanage, Y Ji, D Everett, M Heffernan, U Heinz, S Mak, JF Paquet
Physical Review C 105 (3), 034910, 2022
242022
Supervised compression of big data
VR Joseph, S Mak
Statistical Analysis and Data Mining: The ASA Data Science Journal 14 (3 …, 2021
242021
Kernel-smoothed proper orthogonal decomposition (KSPOD)-based emulation for prediction of spatiotemporally evolving flow dynamics
YH Chang, L Zhang, X Wang, ST Yeh, S Mak, CL Sung, CFJ Wu, V Yang
arXiv preprint arXiv:1802.08812, 2018
24*2018
Kernel-smoothed proper orthogonal decomposition–based emulation for spatiotemporally evolving flow dynamics prediction
YH Chang, L Zhang, X Wang, ST Yeh, S Mak, CL Sung, CF Jeff Wu, ...
AIAA journal 57 (12), 5269-5280, 2019
192019
Projected support points: a new method for high-dimensional data reduction
S Mak, VR Joseph
arXiv preprint arXiv:1708.06897, 2017
17*2017
Hot QCD white paper
M Arslandok, SA Bass, AA Baty, I Bautista, C Beattie, F Becattini, ...
arXiv preprint arXiv:2303.17254, 2023
162023
A graphical multi-fidelity Gaussian process model, with application to emulation of heavy-ion collisions
Y Ji, S Mak, D Soeder, JF Paquet, SA Bass
Technometrics, 1-15, 2023
15*2023
Conglomerate multi-fidelity Gaussian process modeling, with application to heavy-ion collisions
Y Ji, HS Yuchi, D Soeder, JF Paquet, SA Bass, VR Joseph, CFJ Wu, ...
SIAM/ASA Journal on Uncertainty Quantification 12 (2), 473-502, 2024
14*2024
Gaussian Process Subspace Prediction for Model Reduction
R Zhang, S Mak, D Dunson
SIAM Journal on Scientific Computing 44 (3), A1428-A1449, 2022
142022
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