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Simon Mak
Simon Mak
Assistant Professor of Statistical Science, Duke University
Verified email at duke.edu - Homepage
Title
Cited by
Cited by
Year
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
2382021
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
1632021
Support points
S Mak, VR Joseph
The Annals of Statistics 46 (6A), 2562-2592, 2018
1482018
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
1202021
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
1082017
Minimax and minimax projection designs using clustering
S Mak, VR Joseph
Journal of Computational and Graphical Statistics 27 (1), 166-178, 2018
682018
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
342023
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
302018
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
292021
Energy balancing of covariate distributions
JD Huling, S Mak
arXiv preprint arXiv:2004.13962, 2020
272020
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
25*2018
A hierarchical expected improvement method for Bayesian optimization
Z Chen, S Mak, CFJ Wu
Journal of the American Statistical Association, 1-14, 2023
232023
Supervised compression of big data
VR Joseph, S Mak
Statistical Analysis and Data Mining: The ASA Data Science Journal 14 (3 …, 2021
232021
Projected support points: a new method for high-dimensional data reduction
S Mak, VR Joseph
arXiv preprint arXiv:1708.06897, 2017
21*2017
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
192022
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
172019
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
14*2023
Bayesian analysis of QGP jet transport using multi-scale modeling applied to inclusive hadron and reconstructed jet data
R Ehlers, A Angerami, R Arora, SA Bass, S Cao, Y Chen, L Du, T Dai, ...
arXiv preprint arXiv:2208.07950, 2022
142022
Reduced-order modeling for complex flow emulation by common kernel-smoothed proper orthogonal decomposition
YH Chang, X Wang, L Zhang, Y Li, S Mak, CFJ Wu, V Yang
AIAA Journal 59 (9), 3291-3303, 2021
13*2021
Information-Guided Sampling for Low-Rank Matrix Completion
S Mak, HS Yuchi, Y Xie
ICML Workshop on Information Theoretic Methods for Rigorous, Responsible …, 2021
13*2021
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Articles 1–20