wiseodd/generative-models resource

Health v2 · maintenance only

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7494 stars · 2009 forks observed · 2026-08-28

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

A collection of reference implementations of generative models including GANs, VAEs, RBMs, and Helmholtz machines in PyTorch and TensorFlow. It serves primarily as an educational resource with implementations of many GAN and VAE paper variants.

Use cases

• learn how GANs work by reading clean implementations
• study VAE variants like conditional and denoising VAE
• compare GAN implementations in PyTorch and TensorFlow
• implement restricted Boltzmann machines with contrastive divergence
• reproduce classic generative model papers
• find a starting point for a custom GAN project

When to choose

• you want readable, minimal implementations of classic generative models
• you are learning GANs or VAEs from a research/educational angle
• you need reference code for RBMs or the Helmholtz machine

When to avoid

• you need a production-ready generative model library with training utilities
• you want modern architectures like diffusion models or transformers
• you need maintained, tested code with active support

Facets

learning-resource · maturity maintenance

machine-learning deep-learning machine-learning deep-learning artificial-intelligence python gan vae rbm pytorch tensorflow generative-models educational

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