3 papers
stat.ME2026
Hierarchical Bayesian inversion using the Karhunen-Loève expansion with analytical eigenpairs of the squared exponential kernel
Tatsuya Shibata, Michael Conrad Koch, Kazunori Fujisawa
Hierarchical Bayesian inversion with Gaussian random field priors addresses uncertainty in covariance hyperparameters, such as the standard deviation and correlation length. When a…
physics.geo-ph2026
2.5-D Electrical Resistivity Forward Modelling with Undulating Topography using a Modified Half-Space Analytical Solution
Naveen K., Michael C. Koch, Kazunori Fujisawa +2
Field measurements for direct current (DC) resistivity imaging, used for subsurface profiling, are frequently conducted over undulating terrain. Accurately incorporating such topog…
stat.AP2024
Efficient Bayesian inversion for simultaneous estimation of geometry and spatial field using the Karhunen-Loève expansion
Tatsuya Shibata, Michael Conrad Koch, Iason Papaioannou +1
Detection of abrupt spatial changes in physical properties representing unique geometric features such as buried objects, cavities, and fractures is an important problem in geophys…