Gaussian Process Regression with tfprobability
This article is originally published at https://blogs.rstudio.com/tensorflow/Continuing our tour of applications of TensorFlow Probability (TFP), after Bayesian Neural Networks, Hamiltonian Monte Carlo and State Space Models, here we show an example of Gaussian Process Regression. In fact, what we see is a rather "normal" Keras network, defined and trained in pretty much the usual way, with TFP's Variational Gaussian Process layer pulling off all the magic.
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This article is originally published at https://blogs.rstudio.com/tensorflow/
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