rekalantar/VariationalAutoencoders_Pytorch
Variational Autoencoder (VAE) PyTorch Tutorial from Scratch
This project helps machine learning practitioners understand how a Variational Autoencoder (VAE) works from the ground up. It provides code examples in PyTorch to demonstrate the core concepts and implementation. This is ideal for those learning about generative models and latent space visualization.
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Use this if you are a machine learning student or researcher looking for a step-by-step guide to implement a Variational Autoencoder using PyTorch.
Not ideal if you are looking for a pre-built, production-ready VAE model or a library for immediate application to real-world data.
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Jupyter Notebook
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Nov 22, 2023
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