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VAE (MNIST)

A simple VAE project for MNIST. You can switch between a standard VAE (A fully connected (vanilla) VAE) and a ConvVAE (A convolutional VAE (ConvVAE)) by editing the config file.


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All generated images (latent space plots, interpolations, samples) are saved in the results/ folder.

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PyTorch implementation of a Variational Autoencoder (VAE) trained on MNIST to learn and generate handwritten digits, including both standard VAE ( fully connected (vanilla) VAE) and convolutional VAE (ConvVAE) variants with visualization and interpolation tools.

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