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 | 259 | 2021 |
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 | 167 | 2021 |
Support points S Mak, VR Joseph The Annals of Statistics 46 (6A), 2562-2592, 2018 | 153 | 2018 |
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 | 124 | 2021 |
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 | 117 | 2017 |
Minimax and minimax projection designs using clustering S Mak, VR Joseph Journal of Computational and Graphical Statistics 27 (1), 166-178, 2018 | 72 | 2018 |
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 | 41 | 2023 |
Energy balancing of covariate distributions JD Huling, S Mak Journal of Causal Inference 12 (1), 20220029, 2024 | 36 | 2024 |
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 | 35 | 2021 |
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 | 31 | 2018 |
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 | 24 | 2022 |
Supervised compression of big data VR Joseph, S Mak Statistical Analysis and Data Mining: The ASA Data Science Journal 14 (3 …, 2021 | 24 | 2021 |
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 | 19 | 2019 |
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 | 16 | 2023 |
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 | 14 | 2022 |