Probabilistic Programming
Showing 9 of 9 projects
An introduction to Bayesian inference and probabilistic programming using Python and PyMC, with a computational-first approach.
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 library for probabilistic reasoning and statistical analysis integrated with TensorFlow and JAX.
A lightweight probabilistic programming library using NumPy and JAX for autograd and JIT compilation to GPU/TPU/CPU.
A Python tutorial and cookbook for implementing Bayesian modeling techniques using PyMC3.
A Python library for exploratory analysis, diagnostics, and visualization of Bayesian models.
A neuro-symbolic Python framework that combines classical programming with LLMs through composable primitives and design-by-contract validation.
A Go library of probabilistic data structures for processing continuous, unbounded data streams.
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