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 | 107 | 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 | 105 | 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 | 101* | 2014 |
Reduced basis methods for uncertainty quantification P Chen, A Quarteroni, G Rozza SIAM/ASA Journal on Uncertainty Quantification 5 (1), 813-869, 2017 | 96* | 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 | 81 | 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 | 70 | 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 | 67 | 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 | 65 | 2022 |
Projected Stein Variational Gradient Descent P Chen, O Ghattas Advances in Neural Information Processing Systems, 2020 | 64 | 2020 |
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 | 62 | 2019 |
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 | 54 | 2019 |
Optimal design of acoustic metamaterial cloaks under uncertainty P Chen, MR Haberman, O Ghattas Journal of Computational Physics 431, 110114, 2021 | 51 | 2021 |
Sparse-grid, reduced-basis Bayesian inversion P Chen, C Schwab Computer Methods in Applied Mechanics and Engineering 297, 84-115, 2015 | 51 | 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 |
Sparse-grid, reduced-basis Bayesian inversion: Nonaffine-parametric nonlinear equations P Chen, C Schwab Journal of Computational Physics 316, 470–503, 2016 | 49 | 2016 |
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 |
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 | 42 | 2023 |
Model order reduction methods in computational uncertainty quantification P Chen, C Schwab Handbook of Uncertainty Quantification, Springer, 2016 | 37 | 2016 |