genjax-community/genjax
Probabilistic programming with programmable inference for parallel accelerators.
This project helps machine learning researchers and data scientists build and run sophisticated probabilistic models. You define your model's underlying probabilities and data relationships. The project then uses this definition to perform advanced inference, providing insights into model parameters and predictions, especially when dealing with complex, uncertain systems.
Use this if you need to build and analyze probabilistic models with custom inference strategies that run efficiently on GPUs or other parallel accelerators.
Not ideal if you are looking for a high-level library for standard machine learning tasks with pre-built models and simple API calls, or if you prefer a system that is actively maintained and regularly updated.
Stars
47
Forks
7
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 27, 2026
Commits (30d)
0
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