Shane A McQuarrie

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Karen WillcoxOden Institute for Computational Engineering and Sciences, UT AustinVerified email at oden.utexas.edu
Mengwu GuoCentre for Mathematical Sciences, Lund UniversityVerified email at math.lu.se
Jared P WhiteheadBrigham Young UniversityVerified email at mathematics.byu.edu
Cheng HuangUniversity of KansasVerified email at ku.edu
Benjamin PachevGraduate Student, University of Texas at AustinVerified email at utexas.edu
Aseel FarhatAssistant Professor, Florida State UniversityVerified email at fsu.edu
Nathan Glatt-HoltzTulane UniversityVerified email at tulane.edu
Vincent R MartinezCUNY Hunter College, CUNY Graduate CenterVerified email at hunter.cuny.edu
Parisa KhodabakhshiAssistant Professor, Lehigh UniversityVerified email at lehigh.edu
Boris KramerUniversity of California San DiegoVerified email at ucsd.edu
Jessica PurcellProfessor of Mathematics, Monash UniversityVerified email at monash.edu
Bart van Bloemen WaandersSandia National LaboratoriesVerified email at sandia.gov
Zachary MorrowSandia National LaboratoriesVerified email at sandia.gov

Shane A McQuarrie

John von Neumann Postdoctoral Fellow, Sandia National Laboratories

Verified email at sandia.gov - Homepage

applied mathematics scientific machine learning model reduction inverse problems


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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	103	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	43	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	29	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	20	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	17	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	9	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	7	2015
Data-driven parametric reduced-order models: operator inference for reactive flow applications SA McQuarrie		2023
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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