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A Tensorflow implementation of a Variational Autoencoder for the deep learning course at University of Southern California (USC) in the Fall 2017 Semester.

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Variational Autoencoder in Tensorflow

This is an Tensorflow implementation of a variational autoencoder for the deep learning course at USC (CSCI-599 Deep Learning and its Applications) taught by Professor Joseph Lim. The slides of this lecture are available here. This demo code is written by Shao-Hua Sun.

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Reconstruction

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Latent space

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VAE

Generative models

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Shao-Hua Sun / @shaohua0116 @ Joseph Lim's research lab @ USC

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A Tensorflow implementation of a Variational Autoencoder for the deep learning course at University of Southern California (USC) in the Fall 2017 Semester.

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  • Jupyter Notebook 99.2%
  • Python 0.8%