Variational convnets with tfprobability
This article is originally published at https://blogs.rstudio.com/tensorflow/In a Bayesian neural network, layer weights are distributions, not tensors. Using tfprobability, the R wrapper to TensorFlow Probability, we can build regular Keras models that have probabilistic layers, and thus get uncertainty estimates "for free". In this post, we show how to define, train and obtain predictions from a probabilistic convolutional neural network.
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This article is originally published at https://blogs.rstudio.com/tensorflow/
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