Tom Colemont

Modified Bryson-Frazier Smoothing and Hyperparameter Learning for Temporal Gaussian Process Regression

One-dimensional Gaussian processes with stationary, integrable kernel functions admit exact or arbitrarily accurate state-space representations, enabling linear-time inference through Kalman filtering and Rauch-Tung-Striebel (RTS) smoothing. However, the RTS smoother requires inversion of predicted state covariance mat...