Peng Chen

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Alfio QuarteroniProfessor of Mathematics, Politecnico di Milano, Milan, Italy and EPFL, Lausanne, SwitzerlandVerified email at polimi.it
Omar GhattasMechanical Engineering & Oden Institute, Univ of Texas at AustinVerified email at ices.utexas.edu
Gianluigi RozzaFull Professor of Numerical Analysis, SISSA, Int. School for Adv. Studies, Italy and ERC PIVerified email at sissa.it
Umberto VillaOden Institute, UT AustinVerified email at oden.utexas.edu
Keyi WuUniversity of Texas at AustinVerified email at math.utexas.edu
Christoph SchwabProfessor for Mathematics, ETH ZurichVerified email at math.ethz.ch
Thomas O'Leary-RoseberryOden Institute, The University of Texas at AustinVerified email at utexas.edu
Karen Veroy-GreplEindhoven University of Technology (TU/e)Verified email at tue.nl
Michael R. HabermanAssistant Professor, Department of Mechanical Engineering, The University of Texas at AustinVerified email at utexas.edu
Wuchen Li 李务晨University of South Carolina, Assistant professorVerified email at mailbox.sc.edu
Yifei Wang 汪祎非Stanford UniversityVerified email at stanford.edu
Mert PilanciStanford UniversityVerified email at stanford.edu
Johannes O. RoysetNaval Postgraduate SchoolVerified email at nps.edu
Amal AlghamdiDTU ComputeVerified email at dtu.dk
Mirza KaramehmedovićAssociate Professor, Technical University of DenmarkVerified email at dtu.dk
Aaron ZimmermanThe University of Texas at AustinVerified email at austin.utexas.edu
Lianghao CaoPostdoctoral Fellow, Oden Institute, The University of Texas at AustinVerified email at oden.utexas.edu
Dingcheng LuoPhD Student, University of Texas at AustinVerified email at utexas.edu
J. Tinsley OdenVerified email at ices.utexas.edu

Peng Chen

Georgia Institute of Technology

Verified email at cc.gatech.edu - Homepage

scientific machine learning uncertainty quantification stochastic optimization Bayesian inference


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A weighted reduced basis method for elliptic partial differential equations with random input data P Chen, A Quarteroni, G Rozza SIAM Journal on Numerical Analysis 51 (6), 3163-3185, 2013	93	2013
Simulation‐based uncertainty quantification of human arterial network hemodynamics P Chen, A Quarteroni, G Rozza International journal for numerical methods in biomedical engineering 29 (6 …, 2013	91	2013
Comparison between reduced basis and stochastic collocation methods for elliptic problems P Chen, A Quarteroni, G Rozza Journal of Scientific Computing 59, 187-216, 2014	86	2014
Weighted reduced basis method for stochastic optimal control problems with elliptic PDE constraints P Chen, A Quarteroni SIAM/ASA J. Uncertainty Quantification 2 (1), 364–396, 2014	74	2014
Reduced basis methods for uncertainty quantification P Chen, A Quarteroni, G Rozza SIAM/ASA Journal on Uncertainty Quantification 5 (1), 813-869, 2017	61	2017
Multilevel and weighted reduced basis method for stochastic optimal control problems constrained by Stokes equations P Chen, A Quarteroni, G Rozza Numerische Mathematik 133 (1), 67-102, 2015	60	2015
Stochastic optimal Robin boundary control problems of advection-dominated elliptic equations P Chen, A Quarteroni, G Rozza SIAM Journal on Numerical Analysis 51 (5), 2700-2722, 2013	59	2013
A new algorithm for high-dimensional uncertainty quantification based on dimension-adaptive sparse grid approximation and reduced basis methods P Chen, A Quarteroni Journal of Computational Physics 298, 176-193, 2015	51	2015
Projected Stein variational Newton: A fast and scalable Bayesian inference method in high dimensions P Chen, K Wu, J Chen, T O'Leary-Roseberry, O Ghattas Advances in Neural Information Processing Systems, 2019	49	2019
Sparse-grid, reduced-basis Bayesian inversion P Chen, C Schwab Computer Methods in Applied Mechanics and Engineering 297, 84-115, 2015	48	2015
Accurate and efficient evaluation of failure probability for partial different equations with random input data P Chen, A Quarteroni Computer Methods in Applied Mechanics and Engineering 267, 233-260, 2013	46	2013
Taylor approximation and variance reduction for PDE-constrained optimal control under uncertainty P Chen, U Villa, O Ghattas Journal of Computational Physics 385, 163-186, 2019	45	2019
Sparse-grid, reduced-basis Bayesian inversion: Nonaffine-parametric nonlinear equations P Chen, C Schwab Journal of Computational Physics 316, 470–503, 2016	43	2016
Hessian-based adaptive sparse quadrature for infinite-dimensional Bayesian inverse problems P Chen, U Villa, O Ghattas Computer Methods in Applied Mechanics and Engineering 327, 147–172, 2017	41	2017
A weighted empirical interpolation method: A priori convergence analysis and applications P Chen, A Quarteroni, G Rozza ESAIM: Mathematical Modelling and Numerical Analysis 48 (4), 943-953, 2014	38	2014
Derivative-informed projected neural networks for high-dimensional parametric maps governed by PDEs T O’Leary-Roseberry, U Villa, P Chen, O Ghattas Computer Methods in Applied Mechanics and Engineering 388, 114199, 2022	33	2022
The lattice Boltzmann method for fluid dynamics: Theory and applications C Peng M. Math, Department of Mathematics, Ecole Polytechnique Federale de Lausanne …, 2011	33	2011
Projected Stein Variational Gradient Descent P Chen, O Ghattas Advances in Neural Information Processing Systems, 2020	32	2020
Optimal design of acoustic metamaterial cloaks under uncertainty P Chen, MR Haberman, O Ghattas Journal of Computational Physics 431, 110114, 2021	29	2021
Sparse quadrature for high-dimensional integration with Gaussian measure P Chen ESAIM: Mathematical Modelling and Numerical Analysis 52 (2), 631-657, 2018	28	2018

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