171 citations · 898 across the 46 of their papers we have counts for
5 papers · 1 filter
A Fast and Scalable Method for A-Optimal Design of Experiments for Infinite-dimensional Bayesian Nonlinear Inverse Problems
Alen Alexanderian, Noemi Petra, Georg Stadler +1
We address the problem of optimal experimental design (OED) for Bayesian nonlinear inverse problems governed by PDEs. The goal is to find a placement of sensors, at which experimen…
Scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet
Tobin Isaac, Noemi Petra, Georg Stadler +1
The majority of research on efficient and scalable algorithms in computational science and engineering has focused on the forward problem: given parameter inputs, solve the governi…
On Bayesian A- and D-optimal experimental designs in infinite dimensions
Alen Alexanderian, Philip Gloor, Omar Ghattas
We consider Bayesian linear inverse problems in infinite-dimensional separable Hilbert spaces, with a Gaussian prior measure and additive Gaussian noise model, and provide an exten…
Solution of nonlinear Stokes equations discretized by high-order finite elements on nonconforming and anisotropic meshes, with application to ice sheet dynamics
Tobin Isaac, Georg Stadler, Omar Ghattas
Motivated by the need for efficient and accurate simulation of the dynamics of the polar ice sheets, we design high-order finite element discretizations and scalable solvers for th…
Recursive Algorithms for Distributed Forests of Octrees
Tobin Isaac, Carsten Burstedde, Lucas C. Wilcox +1
The forest-of-octrees approach to parallel adaptive mesh refinement and coarsening (AMR) has recently been demonstrated in the context of a number of large-scale PDE-based applicat…