Bayesian Inference
Showing 9 of 9 projects
An introduction to Bayesian inference and probabilistic programming using Python and PyMC, with a computational-first approach.
A comprehensive collection of machine learning algorithms implemented exclusively in NumPy for educational purposes and prototyping.
A flexible, scalable deep probabilistic programming library built on PyTorch for universal probabilistic modeling.
A flexible, scalable deep probabilistic programming library built on PyTorch for universal representation of computable probability distributions.
A Python package for constrained global optimization using Bayesian inference and Gaussian processes.
A library for probabilistic reasoning and statistical analysis integrated with TensorFlow and JAX.
A highly efficient, scalable Gaussian process library implemented in PyTorch with GPU acceleration and modular design.
A lightweight probabilistic programming library using NumPy and JAX for autograd and JIT compilation to GPU/TPU/CPU.
An open-source Python library for probabilistic time series modeling with both frequentist and Bayesian inference methods.
Related Tags
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.