Dan Simpson • 1/20/2023

Markovian Gaussian processes: A lot of theory and some practical stuff

This technical blog post delves into Markovian Gaussian Processes, discussing the computational challenges of standard GPs and how leveraging the Markov property and sparse matrix computations can improve efficiency. It covers theoretical foundations, including reproducing Kernel Hilbert spaces (RKHS), and contrasts covariance function approaches with RKHS-based modeling for greater flexibility.

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#Sparse Matrix #Gaussian Processes #Markov Property