6 citations · 6 across the 2 of their papers we have counts for
4 papers · 1 filter
Novel Deep neural networks for solving Bayesian statistical inverse
Harbir Antil, Howard C Elman, Akwum Onwunta +1
We consider the simulation of Bayesian statistical inverse problems governed by large-scale linear and nonlinear partial differential equations (PDEs). Markov chain Monte Carlo (MC…
Alternating Energy Minimization Methods for Multi-term Matrix Equations
Kookjin Lee, Howard C. Elman, Catherine E. Powell +1
We develop computational methods for approximating the solution of a linear multi-term matrix equation in low rank. We follow an alternating minimization framework, where the solut…
Reduced-order modeling for nonlinear Bayesian statistical inverse problems
Howard C. Elman, Akwum Onwunta
Bayesian statistical inverse problems are often solved with Markov chain Monte Carlo (MCMC)-type schemes. When the problems are governed by large-scale discrete nonlinear partial d…
A Low-rank Solver for the Stochastic Unsteady Navier-Stokes Problem
Howard C. Elman, Tengfei Su
We study a low-rank iterative solver for the unsteady Navier-Stokes equations for incompressible flows with a stochastic viscosity. The equations are discretized using the stochast…