Hi, I’d like to pre-train a UDE model using the collocation method from DiffEqFlux.jl: Smoothed Collocation · DiffEqFlux.jl
My dataset is 10 days worth of temperature measurements and has around 45,000 points which are non-uniformly time distributed (the median time step is around 20 seconds).
Usind the standard TriangularKernel the estimated derivatives look as following (yellow: real data, blue: u and u´ collocation output):
from which is clear that the data (and derivative) have been excessively smoothed. I also tried other kernels without better results (EpanechnikovKernel, GaussianKernel, UniformKernel).
Should I use a specific kernel? Is there an optional argument in collocate_data to control the smoothness I’m missing?
Is such a smoothet out dataset enough to pre-train the UDE?