Shane A McQuarrie 个人学术档案

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	总计	2019 年至今
引用	261	255
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i10 指数	6	6

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Karen WillcoxOden Institute for Computational Engineering and Sciences, UT Austin在 oden.utexas.edu 的电子邮件经过验证
Mengwu GuoCentre for Mathematical Sciences, Lund University在 math.lu.se 的电子邮件经过验证
Jared P WhiteheadBrigham Young University在 mathematics.byu.edu 的电子邮件经过验证
Cheng HuangUniversity of Kansas在 ku.edu 的电子邮件经过验证
Benjamin PachevGraduate Student, University of Texas at Austin在 utexas.edu 的电子邮件经过验证
Parisa KhodabakhshiAssistant Professor, Lehigh University在 lehigh.edu 的电子邮件经过验证
Aseel FarhatAssociate Professor, Florida State University在 fsu.edu 的电子邮件经过验证
Nathan Glatt-HoltzIndiana University, Bloomington在 iu.edu 的电子邮件经过验证
Vincent R MartinezCUNY Hunter College, CUNY Graduate Center在 hunter.cuny.edu 的电子邮件经过验证
Boris KramerUniversity of California San Diego在 ucsd.edu 的电子邮件经过验证
Jessica PurcellProfessor of Mathematics, Monash University在 monash.edu 的电子邮件经过验证
Bart van Bloemen WaandersSandia National Laboratories在 sandia.gov 的电子邮件经过验证
Zachary MorrowSandia National Laboratories在 sandia.gov 的电子邮件经过验证

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Shane A McQuarrie

John von Neumann Postdoctoral Fellow, Sandia National Laboratories

在 sandia.gov 的电子邮件经过验证 - 首页

applied mathematics model reduction uncertainty quantification scientific machine learning


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Data-driven reduced-order models via regularised operator inference for a single-injector combustion process SA McQuarrie, C Huang, KE Willcox Journal of the Royal Society of New Zealand 51 (2), 194-211, 2021	115	2021
Data assimilation in large Prandtl Rayleigh--Bénard convection from thermal measurements A Farhat, NE Glatt-Holtz, VR Martinez, SA McQuarrie, JP Whitehead SIAM Journal on Applied Dynamical Systems 19 (1), 510-540, 2020	48	2020
Bayesian operator inference for data-driven reduced-order modeling M Guo, SA McQuarrie, KE Willcox Computer Methods in Applied Mechanics and Engineering 402, 115336, 2022	35	2022
Concurrent MultiParameter Learning Demonstrated on the Kuramoto–Sivashinsky Equation B Pachev, JP Whitehead, SA McQuarrie SIAM Journal on Scientific Computing 44 (5), A2974-A2990, 2022	24	2022
Nonintrusive reduced-order models for parametric partial differential equations via data-driven operator inference SA McQuarrie, P Khodabakhshi, KE Willcox SIAM Journal on Scientific Computing 45 (4), A1917-A1946, 2023	22	2023
Performance comparison of data-driven reduced models for a single-injector combustion process P Jain, S McQuarrie, B Kramer AIAA Propulsion and Energy 2021 Forum, 3633, 2021	10	2021
Volume and geometry of homogeneously adequate knots P Bartholomew, S McQuarrie, JS Purcell, K Weser Journal of Knot Theory and Its Ramifications 24 (08), 1550044, 2015	6	2015
Data-driven parametric reduced-order models: operator inference for reactive flow applications SA McQuarrie	1	2023
Bayesian learning with Gaussian processes for low-dimensional representations of time-dependent nonlinear systems SA McQuarrie, A Chaudhuri, KE Willcox, M Guo arXiv preprint arXiv:2408.03455, 2024		2024
RaISE: A Framework to Characterize Surrogate Models in Scientific Computing. Z Morrow, B van Bloemen Waanders, J Jakeman, M Salloum, N Winovich, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States); Sandia …, 2022		2022
Goal-oriented data-driven reduced-order modeling guided by hyper-differential sensitivity analysis S McQuarrie, B van Bloemen Waanders Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2021		2021
Information Extraction and Logical Inference for Derivative Classifier Assistance S McQuarrie, AX Garcia, JE Spomer Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2017		2017

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