What is an Autoencoder? | Two Minute Papers #86

Autoencoders are neural networks that are capable of creating sparse representations of the input data and can therefore be used for image compression. There are denoising autoencoders that after learning these sparse representations, can be presented with noisy images. What is even better is a variant that is called the variational autoencoder that not only learns these sparse representations, but can also draw new images as well. We can, for instance, ask it to create new handwritten digits and we can actually expect the results to make sense!

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The paper "Auto-Encoding Variational Bayes" is available here:
http://arxiv.org/pdf/1312.6114.pdf

Recommended for you:
Recurrent Neural Network Writes Sentences About Images - https://www.youtube.com/watch?v=e-WB4lfg30M

Andrej Karpathy's convolutional neural network that you can train in your browser:
http://cs.stanford.edu/people/karpathy/convnetjs/demo/cifar10.html

Sentdex's Youtube channel is available here:
https://www.youtube.com/user/sentdex

Francois Chollet's blog post on autoencoders:
https://blog.keras.io/building-autoencoders-in-keras.html

More reading on autoencoders:
https://probablydance.com/2016/04/30/neural-networks-are-impressively-good-at-compression/

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