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Gradient of decoder

Welcome to the fifth week of the course! This week we will combine many ideas from the previous weeks and add some new to build Variational Autoencoder -- a model that can learn a distribution over structured data (like photographs or molecules) and then sample new data points from the learned distribution, hallucinating new photographs of non-existing people. We will also the same techniques to Bayesian Neural Networks and will see how this can greatly compress the weights of the network without reducing the accuracy.

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