AmirhosseinHonardoust/Teaching-Neural-Networks-to-Imagine-Tables

A comprehensive deep dive into how Variational Autoencoders (VAEs) learn to generate realistic synthetic tabular data. This project explores latent space learning, probabilistic modeling, and neural creativity, combining data privacy, interpretability, and generative AI techniques in a structured format.

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Maintenance 6 / 25
Adoption 6 / 25
Maturity 9 / 25
Community 0 / 25

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MIT

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variational-autoencoder-implementations

Last pushed

Nov 10, 2025

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Variational Autoencoder Implementations · 77 frameworks

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