Accelerating PDE-constrained Inverse Solutions with Deep Learning and Reduced Order Models

no code implementations • 17 Dec 2019 • Sheroze Sheriffdeen, Jean C. Ragusa, Jim E. Morel, Marvin L. Adams, Tan Bui-Thanh

In this paper, we propose to enlarge the validity of ROMs and hence improve the accuracy outside the reduced subspaces by incorporating a data-driven ML technique.

Solving Bayesian Inverse Problems via Variational Autoencoders

no code implementations • 5 Dec 2019 • Hwan Goh, Sheroze Sheriffdeen, Jonathan Wittmer, Tan Bui-Thanh

Further, this framework possesses an inherent adaptive optimization property that emerges through the learning of the posterior uncertainty.

Uncertainty Quantification Variational Inference