Thanks for the reply! I’m trying to calibrate a FEM model for the Euler-Bernoulli Equation using the framework by Kennedy & O’Hagan (The paper in question). The first step of the process is to obtain the parameters of a GP of the computer model with it’s dimensions being time and various physical parameters. Here I’m only trying to use the viscous dampening parameter as an extra dimension.
Since this problem is bound to scale pourly when increasing the number of dimensions being used I wanted to implement some of the methods used for improving scalling like the sparse approximation.
In the uploaded file is a reproduction of what I want to achieve with the model (using a dummy equation to generate model data)
KOH_Example.py (2.8 KB)
Thanks again!!