458 citations · 2.3k across the 71 of their papers we have counts for
3 papers · 2 filters
Scalable posterior approximations for large-scale Bayesian inverse problems via likelihood-informed parameter and state reduction
Tiangang Cui, Youssef M. Marzouk, Karen E. Willcox
Two major bottlenecks to the solution of large-scale Bayesian inverse problems are the scaling of posterior sampling algorithms to high-dimensional parameter spaces and the computa…
On dimension reduction in Gaussian filters
Antti Solonen, Tiangang Cui, Janne Hakkarainen +1
A priori dimension reduction is a widely adopted technique for reducing the computational complexity of stationary inverse problems. In this setting, the solution of an inverse pro…
A multiscale strategy for Bayesian inference using transport maps
Matthew Parno, Tarek Moselhy, Youssef Marzouk
In many inverse problems, model parameters cannot be precisely determined from observational data. Bayesian inference provides a mechanism for capturing the resulting parameter unc…