/Deep-Generative-Models

Keras and Theano implementations of various Deep Generative Models(e.g. Variational Autoencoders, Restricted Boltzmann Machines, and Generative Adversarial Networks)

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Deep-Generative-Models

Implementations(chiefly in Keras w/Tensorflow backend) of various Deep Generative Models(e.g. Variational Autoencoders, RBMs, and Generative Adversarial Networks)

  1. Variational_Autoencoder.py employs a Variational Autoencoder (Kingma, Welling 2013) to reconstruct MNIST handwritten digits.

  2. Deep_Convolutional_GAN.py uses a Deep Convolutional Generative Adversarial Network (Radford et. al, 2015) to reconstruct MNIST handwritten digits.