State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes

12 Jul 2020William J. WilkinsonPaul E. ChangMichael Riis AndersenArno Solin

We formulate approximate Bayesian inference in non-conjugate temporal and spatio-temporal Gaussian process models as a simple parameter update rule applied during Kalman smoothing. This viewpoint encompasses most inference schemes, including expectation propagation (EP), the classical (Extended, Unscented, etc.).. (read more)

PDF Abstract

Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper