How to implement & train a convolutional variational autoencoder with Keras in under 50 lines of code: https://colab.research.google.com/drive/1COeSoasrpY-w3uF1JPVksLEjx4Tx2ns5 …pic.twitter.com/MK580AGH53
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1. The encoder & decoder 2. The VAE (with a custom train_step) 3. Training itpic.twitter.com/J8D4MjZWpt
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Here's a slightly tweaked version that does a better job at showing the latent manifold of MNIST digits (I'll put this one in the next edition of my book to illustrate the manifold hypothesis)pic.twitter.com/3bx5LYwaNf
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I'll take this as a sign to get a copy of the second edition. Great work!
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You can add a huber loss as the paper modeling AIQN VAE. It s more efficient to go with quantiles when sampling a normal law.
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Whats the release date or expected timeline for you new book?
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