Bayesian inversion with Student'st priors based on Gaussian scale mixtures
Many inverse problems focus on recovering a quantity of interest that is a priori known to
exhibit either discontinuous or smooth behavior. Within the Bayesian approach to inverse …
exhibit either discontinuous or smooth behavior. Within the Bayesian approach to inverse …
A hierarchical Bayesian framework embedded with an improved orthogonal series expansion for Gaussian processes and fields identification
A new hierarchical Bayesian framework (HBM) is proposed for identification of Gaussian
processes or fields, which are usually used for simulating uncertainty in temporal variability …
processes or fields, which are usually used for simulating uncertainty in temporal variability …
A parameterization of anisotropic Gaussian fields with penalized complexity priors
L Llamazares-Elias, J Latz, F Lindgren - ar**. A difficulty in the prediction of pi** is characterising the subsoil under …
Bayesian analysis and rare event simulation of random fields
F Uribe-Castillo - 2020 - mediatum.ub.tum.de
Bayesian inference and rare event simulation increase in complexity when model
parameters are represented through random fields. We propose two algorithms that are …
parameters are represented through random fields. We propose two algorithms that are …
[PDF][PDF] Simulation Methods for Reliability-Based Design Optimization and Model Updating of Civil Engineering Structures and Systems
DJJ Urquieta - core.ac.uk
This thesis presents a collection of original contributions pertaining to the subjects of
reliabilitybased design optimization (RBDO) and model updating of civil engineering …
reliabilitybased design optimization (RBDO) and model updating of civil engineering …