Karen Willcox

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99 件の論文

7 件の論文

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Benjamin PeherstorferCourant Institute of Mathematical Sciences, New York University確認したメールアドレス: cims.nyu.edu
Douglas AllaireAssociate Professor, Texas A&M University確認したメールアドレス: tamu.edu
Omar GhattasProfessor & Cockrell endowed chair, Mechanical Engineering & Oden Institute, Univ of Texas at Austin確認したメールアドレス: ices.utexas.edu
Boris KramerUniversity of California San Diego確認したメールアドレス: ucsd.edu
Jaume Peraire Jaime PeraireH.N. Slater Professor of Aeronautics and Astronautics, MIT確認したメールアドレス: mit.edu
Anirban ChaudhuriOden Institute for Computational Engineering and Sciences, UT Austin確認したメールアドレス: oden.utexas.edu
Tan Bui-ThanhAssociate Professor. The Department of Aerospace Engineering and Engineering Mechanics確認したメールアドレス: oden.utexas.edu
Michael G. KapteynPhD, Massachusetts Institute of Technology確認したメールアドレス: mit.edu
Peter BennerMax Planck Institute for Dynamics of Complex Technical Systems確認したメールアドレス: mpi-magdeburg.mpg.de
Youssef MarzoukProfessor, Massachusetts Institute of Technology確認したメールアドレス: mit.edu
Serkan GugercinClass of 1950 Professor of Mathematics, Virginia Tech確認したメールアドレス: vt.edu
Bart van Bloemen WaandersSandia National Laboratories確認したメールアドレス: sandia.gov
Laura MaininiProfessor of Aerospace Computational Design, Imperial College London確認したメールアドレス: imperial.ac.uk
Rémi LamDeepMind確認したメールアドレス: deepmind.com
Murali DamodaranNational University of Singapore確認したメールアドレス: nus.edu.sg
Max OpgenoordSenior Applied Scientist, Amazon確認したメールアドレス: mit.edu
Tiangang CuiUniversity of Sydney確認したメールアドレス: sydney.edu.au
Elizabeth QianGeorgia Institute of Technology確認したメールアドレス: gatech.edu
Alexandre MarquesNeural Magic確認したメールアドレス: neuralmagic.com
Luwen HuangUT Austin確認したメールアドレス: austin.utexas.edu

フォロー

Karen Willcox

Oden Institute for Computational Engineering and Sciences, UT Austin

確認したメールアドレス: oden.utexas.edu - ホームページ

model reduction multifidelity methods digital twin uncertainty quantification educational analytics


タイトル引用回数順公開年順タイトル順	引用先引用先	年
A SURVEY OF PROJECTION-BASED MODEL REDUCTION METHODS FOR PARAMETRIC DYNAMICAL SYSTEMS P BENNER, S GUGERCIN, K WILLCOX SIAM Review 57 (4), 483–531, 2015	2038	2015
Balanced model reduction via the proper orthogonal decomposition K Willcox, J Peraire AIAA Journal 40 (11), 2323-2330, 2002	1298	2002
Survey of multifidelity methods in uncertainty propagation, inference, and optimization B Peherstorfer, K Willcox, M Gunzburger SIAM Review 60 (3), 550-591, 2018	1125	2018
Aerodynamic data reconstruction and inverse design using proper orthogonal decomposition T Bui-Thanh, M Damodaran, KE Willcox AIAA Journal 42 (8), 1505-1516, 2004	594	2004
Missing point estimation in models described by proper orthogonal decomposition P Astrid, S Weiland, K Willcox, T Backx IEEE Transactions on Automatic Control 53 (10), 2237-2251, 2008	570	2008
Model Reduction and Approximation: Theory and Algorithms P Benner, M Ohlberger, A Cohen, K Willcox Society for Industrial and Applied Mathematics, 2017	569	2017
Unsteady flow sensing and estimation via the gappy proper orthogonal decomposition K Willcox Computers & fluids 35 (2), 208-226, 2006	515	2006
Model reduction for large-scale systems with high-dimensional parametric input space T Bui-Thanh, K Willcox, O Ghattas SIAM Journal on Scientific Computing 30 (6), 3270-3288, 2008	493	2008
Data-driven operator inference for nonintrusive projection-based model reduction B Peherstorfer, K Willcox Computer Methods in Applied Mechanics and Engineering 306, 196-215, 2016	451	2016
Projection-based model reduction: Formulations for physics-based machine learning R Swischuk, L Mainini, B Peherstorfer, K Willcox Computers & Fluids 179, 704-717, 2019	380	2019
Optimal model management for multifidelity Monte Carlo estimation B Peherstorfer, K Willcox, M Gunzburger SIAM Journal on Scientific Computing 38 (5), A3163-A3194, 2016	317	2016
Parameter and state model reduction for large-scale statistical inverse problems C Lieberman, K Willcox, O Ghattas SIAM Journal on Scientific Computing 32 (5), 2523-2542, 2010	317	2010
Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems E Qian, B Kramer, B Peherstorfer, K Willcox Physica D: Nonlinear Phenomena 406, 132401, 2020	314	2020
Proper orthogonal decomposition extensions for parametric applications in compressible aerodynamics T Bui-Thanh, M Damodaran, K Willcox 21st AIAA Applied Aerodynamics Conference, 4213, 2003	312	2003
Proper orthogonal decomposition extensions for parametric applications in transonic aerodynamics T Bui-Thanh, M Damodaran, K Willcox 21th AIAA Applied Aerodynamics Conference, AIAA Paper 2003-4213, 2003	312*	2003
Surrogate-based optimization using multifidelity models with variable parameterization and corrected space mapping TD Robinson, MS Eldred, KE Willcox, R Haimes Aiaa Journal 46 (11), 2814-2822, 2008	294	2008
Localized discrete empirical interpolation method B Peherstorfer, D Butnaru, K Willcox, HJ Bungartz SIAM Journal on Scientific Computing 36 (1), A168-A192, 2014	291	2014
Non-linear model reduction for uncertainty quantification in large-scale inverse problems D Galbally, K Fidkowski, K Willcox, O Ghattas John Wiley & Sons, Ltd., 2010	290	2010
A probabilistic graphical model foundation for enabling predictive digital twins at scale MG Kapteyn, JVR Pretorius, KE Willcox Nature Computational Science 1 (5), 337-347, 2021	250	2021
Multifidelity approaches for optimization under uncertainty LWT Ng, KE Willcox International Journal for Numerical Methods in Engineering 100 (10), 746-772, 2014	247	2014

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