homerjed/sbgm
Score-based Diffusion models in JAX.
This project helps machine learning researchers implement and extend score-based diffusion models. It takes in existing datasets (like images) and outputs new, similar data samples or calculated data likelihoods. Researchers working with generative models for complex data like images would use this to experiment with diffusion model architectures and training.
Available on PyPI.
Use this if you are a machine learning researcher or practitioner looking to build, train, and experiment with score-based diffusion models for generating data or estimating likelihoods.
Not ideal if you need an out-of-the-box solution for generating data without needing to understand or customize the underlying diffusion model architecture.
Stars
18
Forks
1
Language
Python
License
MIT
Category
Last pushed
Dec 29, 2025
Commits (30d)
0
Dependencies
16
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