Peng Chen

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Omar GhattasProfessor & Pratt endowed chair, Mechanical Engineering & Oden Institute, Univ of Texas at AustinDirección de correo verificada de ices.utexas.edu
Alfio QuarteroniProfessor of Mathematics, Politecnico di Milano, Milan, Italy and EPFL, Lausanne, SwitzerlandDirección de correo verificada de polimi.it
Gianluigi RozzaFull Professor of Numerical Analysis, SISSA, Int. School for Adv. Studies, Italy and ERC PIDirección de correo verificada de sissa.it
Keyi WuUniversity of Texas at AustinDirección de correo verificada de math.utexas.edu
Umberto VillaOden Institute, UT AustinDirección de correo verificada de oden.utexas.edu
Thomas O'Leary-RoseberryOden Institute, The University of Texas at AustinDirección de correo verificada de utexas.edu
Christoph SchwabProfessor for Mathematics, ETH ZurichDirección de correo verificada de math.ethz.ch
Karen Veroy-GreplEindhoven University of Technology (TU/e)Dirección de correo verificada de tue.nl
Wuchen Li 李务晨University of South Carolina, Assistant professorDirección de correo verificada de mailbox.sc.edu
Yifei Wang 汪祎非Stanford UniversityDirección de correo verificada de stanford.edu
Michael R. HabermanAssociate Professor, Department of Mechanical Engineering, The University of Texas at AustinDirección de correo verificada de utexas.edu
Lianghao CaoPostdoctoral Scholar Research Associate, California Institute of TechnologyDirección de correo verificada de caltech.edu
J. Tinsley OdenDirección de correo verificada de ices.utexas.edu
Dingcheng LuoPhD Student, University of Texas at AustinDirección de correo verificada de utexas.edu
Denise DegenPostdoctoral Researcher, RWTH Aachen UniversityDirección de correo verificada de cgre.rwth-aachen.de
Mert PilanciStanford UniversityDirección de correo verificada de stanford.edu
Johannes O. RoysetUniversity of Southern CaliforniaDirección de correo verificada de usc.edu
Amal AlghamdiDTU ComputeDirección de correo verificada de dtu.dk
Mirza KaramehmedovićAssociate Professor, Technical University of DenmarkDirección de correo verificada de dtu.dk
Felix J. HerrmannProfessor Schools of Earth and Atmospheric Sciences, Computational Science and EngineeringDirección de correo verificada de gatech.edu

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Peng Chen

Georgia Institute of Technology

Dirección de correo verificada de cc.gatech.edu - Página principal

scientific machine learning uncertainty quantification stochastic optimization Bayesian inference


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
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	105	2013
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	103	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	100*	2014
Reduced basis methods for uncertainty quantification P Chen, A Quarteroni, G Rozza SIAM/ASA Journal on Uncertainty Quantification 5 (1), 813-869, 2017	87*	2017
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	79	2014
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	67	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	66	2013
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	61	2022
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	61	2019
Projected Stein Variational Gradient Descent P Chen, O Ghattas Advances in Neural Information Processing Systems, 2020	60	2020
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	55	2015
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	53	2019
Sparse-grid, reduced-basis Bayesian inversion P Chen, C Schwab Computer Methods in Applied Mechanics and Engineering 297, 84-115, 2015	52	2015
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	50	2017
Optimal design of acoustic metamaterial cloaks under uncertainty P Chen, MR Haberman, O Ghattas Journal of Computational Physics 431, 110114, 2021	49	2021
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	48	2013
Sparse-grid, reduced-basis Bayesian inversion: Nonaffine-parametric nonlinear equations P Chen, C Schwab Journal of Computational Physics 316, 470–503, 2016	47	2016
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	44	2014
A fast and scalable computational framework for large-scale high-dimensional Bayesian optimal experimental design K Wu, P Chen, O Ghattas SIAM/ASA Journal on Uncertainty Quantification 11 (1), 235-261, 2023	41	2023
The lattice Boltzmann method for fluid dynamics: Theory and applications C Peng M. Math, Department of Mathematics, Ecole Polytechnique Federale de Lausanne …, 2011	36	2011

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