YannDubs/disentangling-vae
Experiments for understanding disentanglement in VAE latent representations
This project helps researchers and machine learning practitioners understand how well different Variational Autoencoder (VAE) models can separate distinct characteristics of an input image into independent factors. You input images (e.g., faces, MNIST digits) and it outputs visual representations of these disentangled factors, along with metrics to quantify their separation. This is ideal for those studying representation learning and generative models.
841 stars. No commits in the last 6 months.
Use this if you are a machine learning researcher or practitioner investigating and comparing various disentanglement techniques for VAEs.
Not ideal if you need a plug-and-play generative model for a specific application without deep experimentation into disentanglement.
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841
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Language
Python
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Last pushed
Feb 02, 2023
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