AmirhosseinHonardoust / Teaching-Neural-Networks-to-Imagine-Tables
View external linksLinks

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.
20Nov 10, 2025Updated 3 months ago

Alternatives and similar repositories for Teaching-Neural-Networks-to-Imagine-Tables

Users that are interested in Teaching-Neural-Networks-to-Imagine-Tables are comparing it to the libraries listed below

Sorting:

Are these results useful?