41 citations · 198 across the 24 of their papers we have counts for
Showing 2022Show all
2 papers · 1 filter
stat.CO2022★ 2 cited
Gradient-based data and parameter dimension reduction for Bayesian models: an information theoretic perspective
Ricardo Baptista, Youssef Marzouk, Olivier Zahm
We consider the problem of reducing the dimensions of parameters and data in non-Gaussian Bayesian inference problems. Our goal is to identify an "informed" subspace of the paramet…
math.NA2022★ 12 cited
Prior normalization for certified likelihood-informed subspace detection of Bayesian inverse problems
Tiangang Cui, Xin Tong, Olivier Zahm
Markov chain Monte Carlo (MCMC) methods form one of the algorithmic foundations of Bayesian inverse problems. The recent development of likelihood-informed subspace (LIS) methods o…