Sparse Latent Gaussian Process Model - Issue Specifying Guide when latent states are correlated

Hey guys,

I’ve been able to successfully implement my own sparse latent gaussian process model with an arbitrary number of latent dimensions (with inducing inputs). However, I want to allow correlation over time of the latent state. This paper gives an idea on how to do it:

(Variational Gaussian Process Dynamical Systems - see section 2.2)

However, the parametrization of the guide appears to require the inversion of an NxN matrix, which isn’t feasible for any reasonable sized problem (which is obviously why the inducing-input approach was developed).

Am I missing something here? How can this be done?