no code implementations • 5 May 2023 • Ahmed Attia, Sven Leyffer, Todd Munson
This work presents an efficient algorithmic approach for designing optimal experimental design schemes for Bayesian inverse problems such that the optimal design is robust to misspecification of elements of the inverse problem.
no code implementations • 15 Jan 2021 • Ahmed Attia, Sven Leyffer, Todd Munson
We present a novel stochastic approach to binary optimization for optimal experimental design (OED) for Bayesian inverse problems governed by mathematical models such as partial differential equations.
no code implementations • 2 Jan 2018 • Azam Moosavi, Ahmed Attia, Adrian Sandu
In typical weather forecasting applications, the model state space has dimension $10^{9}-10^{12}$, while the ensemble size typically ranges between $30-100$ members.