StateSpace Inference and Learning with Gaussian Processes Ryan Turner Marc Peter Deisenroth Carl Edward Rasmussen Department of Engineering University of Cambridge Trumpington Street Cambridge CB PZ

We propose a new general metho dology for inference and learning in nonlinear statespace models that are described prob abilistically by nonparametric GP models We apply the expectation maximization al gorithm to iterate between inference in the lat

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