probabilists/zuko
Normalizing flows in PyTorch
This project helps machine learning engineers and researchers build advanced probabilistic models. It takes in structured data and outputs flexible, high-dimensional probability distributions that can be easily trained and sampled. It is ideal for those working on complex density estimation or generative modeling tasks.
446 stars. Used by 2 other packages. Available on PyPI.
Use this if you need to create and manage conditional probability distributions or transformations within PyTorch, especially for deep learning models.
Not ideal if you are not already working with PyTorch and deep learning, or if you only need simple, pre-defined probability distributions.
Stars
446
Forks
35
Language
Python
License
MIT
Category
Last pushed
Mar 10, 2026
Commits (30d)
0
Dependencies
2
Reverse dependents
2
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