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A comprehensive list of PyTorch-related content on GitHub, including models, libraries, and tutorials.
A powerful Bayesian modeling and probabilistic programming library for Python developers.
A deep universal probabilistic programming library for Python and PyTorch, enabling Bayesian machine learning.
A probabilistic language based on pattern matching and constraint propagation for procedural generation.
Python code for a book on probabilistic machine learning, with support for various ML frameworks.
Edward is a probabilistic programming language in TensorFlow for deep generative models and variational inference.
Probabilistic reasoning and statistical analysis tools built on TensorFlow for data scientists and ML researchers.
A probabilistic programming library powered by NumPy and JAX for Bayesian inference and MCMC sampling.
Turing.jl is a powerful Bayesian inference library for probabilistic programming in the Julia language.
A general-purpose probabilistic programming system for building AI and ML applications.
A curated list of awesome PyTorch libraries, models, and tutorials in Chinese translation.
A neurosymbolic perspective on large language models for AI-powered coding and development
Performant probabilistic data structures for processing continuous, unbounded streams in Go.
High-quality implementations of standard and state-of-the-art methods for Bayesian and probabilistic machine learning.
BlackJAX is a Bayesian inference library for Python, focused on ease of use, speed, and modularity.
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