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Pyro is a deep probabilistic programming library and differentiable probabilistic modeler designed for Bayesian inference. It functions as a probabilistic programming language that allows for the construction of complex graphical models using PyTorch tensors and automatic differentiation. The framework enables the definition of universal probabilistic models as standard Python functions. It integrates deep learning with probabilistic modeling to compute posterior distributions and estimate latent variables through gradient-based optimization and algorithmic solvers. The system provides a pro
This project is a computational statistics textbook and Bayesian data analysis course. It serves as a guide for performing statistical inference and quantifying uncertainty through a probabilistic programming workflow using Python. The resource employs a computation-first pedagogy, teaching Bayesian methods and parameter estimation through executable code and simulations instead of formal mathematical notation. It provides a practical approach to implementing Markov Chain Monte Carlo sampling to estimate posterior distributions. The content covers building probabilistic models, integrating e
Pyro is a probabilistic programming language and library built for PyTorch. It serves as a Bayesian inference engine and a tool for probabilistic graphical modeling, allowing users to define generative models that combine neural networks with probabilistic logic. The framework enables deep probabilistic programming by integrating probability distributions into computational graphs. This allows for the quantification of uncertainty in deep learning models and the execution of scalable posterior distribution calculations for complex data dependencies. The system provides a suite of inference c
Exploratory analysis of Bayesian models with Python
Probabilistic programming powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
The main features of pyro-ppl/numpyro are: Probabilistic Modeling, Probabilistic Programming, Statistical Modeling.
Open-source alternatives to pyro-ppl/numpyro include: pyro-ppl/pyro — Pyro is a deep probabilistic programming library and differentiable probabilistic modeler designed for Bayesian… uber/pyro — Pyro is a probabilistic programming language and library built for PyTorch. It serves as a Bayesian inference engine… camdavidsonpilon/probabilistic-programming-and-bayesian-methods-for-hackers — This project is a computational statistics textbook and Bayesian data analysis course. It serves as a guide for… pymc-devs/pymc — PyMC is a Bayesian probabilistic programming framework used for building probabilistic models and performing Bayesian… jmschrei/pomegranate — Fast, flexible and easy to use probabilistic modelling in Python. arviz-devs/arviz — Exploratory analysis of Bayesian models with Python.