Inference with a GP model is thus expensive, but this can be addressed by learning a small number M of pseudo data points and using them to train the model instead (Snelson and Ghahramani, 2006).
2 we can approximate the inverse of the covariance matrix with the inverse of the M ×M "pseudo matrix" instead.