16 citations · 16 across the 1 of their papers we have counts for
5 papers
Hierarchical Matrix Approximations of Hessians Arising in Inverse Problems Governed by PDEs
Ilona Ambartsumyan, Wajih Boukaram, Tan Bui-Thanh +5
Hessian operators arising in inverse problems governed by partial differential equations (PDEs) play a critical role in delivering efficient, dimension-independent convergence for…
Accelerating PDE-constrained Inverse Solutions with Deep Learning and Reduced Order Models
Sheroze Sheriffdeen, Jean C. Ragusa, Jim E. Morel +2
Inverse problems are pervasive mathematical methods in inferring knowledge from observational and experimental data by leveraging simulations and models. Unlike direct inference me…
Sequential Ensemble Transform for Bayesian Inverse Problems
Aaron Myers, Alexandre H. Thiery, Kainan Wang +1
We present the Sequential Ensemble Transform (SET) method, an approach for generating approximate samples from a Bayesian posterior distribution. The method explores the posterior…
A Multilevel Approach for Trace System in HDG Discretizations
Sriramkrishnan Muralikrishnan, Tan Bui-Thanh, John N. Shadid
We propose a multilevel approach for trace systems resulting from hybridized discontinuous Galerkin (HDG) methods. The key is to blend ideas from nested dissection, domain decompos…
A randomized maximum a posterior method for posterior sampling of high dimensional nonlinear Bayesian inverse problems
Kainan Wang, Tan Bui-Thanh, Omar Ghattas
We present a randomized maximum a posteriori (rMAP) method for generating approximate samples of posteriors in high dimensional Bayesian inverse problems governed by large-scale fo…