1 citations · 1 across the 1 of their papers we have counts for
3 papers
math.NA2020★ 1 cited
Stein variational reduced basis Bayesian inversion
Peng Chen, Omar Ghattas
We propose and analyze a Stein variational reduced basis method (SVRB) to solve large-scale PDE-constrained Bayesian inverse problems. To address the computational challenge of dra…
cs.LG2020
Projected Stein Variational Gradient Descent
Peng Chen, Omar Ghattas
The curse of dimensionality is a longstanding challenge in Bayesian inference in high dimensions. In this work, we propose a projected Stein variational gradient descent (pSVGD) me…
math.OC2019
Projected Stein Variational Newton: A Fast and Scalable Bayesian Inference Method in High Dimensions
Peng Chen, Keyi Wu, Joshua Chen +2
We propose a fast and scalable variational method for Bayesian inference in high-dimensional parameter space, which we call projected Stein variational Newton (pSVN) method. We exp…