36 citations · 99 across the 7 of their papers we have counts for
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math.NA2022
Large-scale Bayesian optimal experimental design with derivative-informed projected neural network
Keyi Wu, Thomas O'Leary-Roseberry, Peng Chen +1
We address the solution of large-scale Bayesian optimal experimental design (OED) problems governed by partial differential equations (PDEs) with infinite-dimensional parameter fie…
math.NA2020★ 16 cited
A fast and scalable computational framework for large-scale and high-dimensional Bayesian optimal experimental design
Keyi Wu, Peng Chen, Omar Ghattas
We develop a fast and scalable computational framework to solve large-scale and high-dimensional Bayesian optimal experimental design problems. In particular, we consider the probl…
math.NA2015★ 17 cited
A surrogate accelerated multicanonical Monte Carlo method for uncertainty quantification
Keyi Wu, Jinglai Li
In this work we consider a class of uncertainty quantification problems where the system performance or reliability is characterized by a scalar parameter . The performance para…