Stochastic Blog
Hidden states, filters, and Gaussian Processes
Post 20 gave us the probability toolkit, and Post 21 pushed uncertainty into deep models. This post keeps the same question, uncertainty, and moves it onto sequences and functions. We will read a temporal model as a graph, fit a Gaussian hidden Markov model to hourly power use, run four