8 papers
Amortized low-rank approximation for hyperparameter marginalization in PDE-governed Bayesian inverse problems
Sonia Reilly, Georg Stadler
This paper addresses the efficient solution of hierarchical Bayesian inverse problems with a high- or infinite-dimensional parameter field and a moderate number of hyperparameters.…
Optimal experimental design for passive imaging source problems
Christian Aarset, Thorsten Hohage, Georg Stadler
This work focuses on optimal experimental design (OED) methods for passive imaging. We adopt a Bayesian inverse problem framework for passive imaging source problems, primarily foc…
Learning parameter-dependent shear viscosity from data, with application to sea and land ice
Gonzalo G. de Diego, Georg Stadler
Complex physical systems which exhibit fluid-like behavior are often modeled as non-Newtonian fluids. A crucial element of a non-Newtonian model is the rheology, which relates inne…
Physics-informed reservoir characterization from bulk and extreme pressure events with a differentiable simulator
Harun Ur Rashid, Mingxin Li, Aleksandra Pachalieva +2
Accurate characterization of subsurface heterogeneity is challenging but essential for applications such as reservoir pressure management, geothermal energy extraction and CO,…
Infinite-dimensional spherical-radial decomposition for probabilistic functions, with application to constrained optimal control and Gaussian process regression
Kewei Wang, Georg Stadler
The spherical-radial decomposition (SRD) is an efficient method for estimating probabilistic functions and their gradients defined over finite-dimensional elliptical distributions.…
Non-Newtonian viscous fluid models with learned rheology accurately reproduce Lagrangian sea ice simulations
Gonzalo G. de Diego, Georg Stadler
Polar sea ice is crucial to Earth's climate system. Its dynamics also affect coastal communities, wildlife, and global shipping. Sea ice is typically modeled as a continuum fluid u…