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This project provides a basic study of deep generative models and a comparative study of different types of deep generative models, which are VAE(Variational Autoencoder), GAN(Generative Adversarial Networks) and Flow based models. All the models have trained with MNIST handwritten digit database containing images of size 28x28 pixels.

License: Apache License 2.0

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