Variational Fourier features for Gaussian processes

Understand

This work brings together two powerful concepts in Gaussian processes: the variational approach to sparse approximation and the spectral representation of Gaussian processes.

• This gives rise to an approximation that inherits the benefits of the variational approach but with the representational power and computational scalability of spectral representations.
• The work hinges on a key result that there exist spectral features related to a finite domain of the Gaussian process which exhibit almost-independent covariances.
• We derive these expressions for Matern kernels in one dimension, and generalize to more dimensions using kernels with specific structures.