thuwzy/ZhuSuan-PyTorch
An Elegant Library for Bayesian Deep Learning in PyTorch
This library helps machine learning researchers and practitioners who want to build and experiment with Bayesian deep learning models. It takes raw data and model specifications as input, and outputs trained models or probabilistic inferences. The end-user is typically an AI or machine learning engineer, researcher, or data scientist working with probabilistic models.
No commits in the last 6 months.
Use this if you are a machine learning researcher or practitioner needing to implement Bayesian deep learning models and perform advanced probabilistic inference techniques like Variational Inference or MCMC within a PyTorch environment.
Not ideal if you are looking for a high-level, out-of-the-box solution for common machine learning tasks without diving into the specifics of probabilistic programming or Bayesian methods.
Stars
27
Forks
4
Language
Python
License
MIT
Category
Last pushed
Dec 19, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/thuwzy/ZhuSuan-PyTorch"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
tensorflow/probability
Probabilistic reasoning and statistical analysis in TensorFlow
erdogant/bnlearn
Python package for Causal Discovery by learning the graphical structure of Bayesian networks....
pyro-ppl/pyro
Deep universal probabilistic programming with Python and PyTorch
probml/pyprobml
Python code for "Probabilistic Machine learning" book by Kevin Murphy
google/edward2
A simple probabilistic programming language.