hwalsuklee/tensorflow-generative-model-collections resource

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3918 stars · 835 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A collection of TensorFlow implementations of various generative models, including many GAN variants (GAN, WGAN, WGAN-GP, CGAN, infoGAN, ACGAN, EBGAN, BEGAN, etc.) and VAEs. It provides consistent architectures and reproducible results on MNIST and Fashion-MNIST for comparing generative model ideas.

Use cases

• learn how GAN variants differ in their value functions
• reproduce and compare GAN results on MNIST
• find a reference implementation of WGAN-GP or infoGAN
• study VAE and CVAE implementations in TensorFlow
• get starter code for experimenting with generative adversarial networks

When to choose

• you want clean, comparable reference implementations of many GAN/VAE variants
• you are studying or teaching generative models with small image datasets
• you need TensorFlow 1.x-era code matching original papers

When to avoid

• you need production-ready or modern TensorFlow 2/PyTorch generative model tooling
• you want to train on large, high-resolution datasets
• you need actively maintained code with recent fixes

Facets

learning-resource · maturity maintenance

machine-learning deep-learning image-processing deep-learning machine-learning computer-vision tutorials python gan vae tensorflow generative-models mnist reference-implementations gpu

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