PyAutoFit
PyAutoFit: A Classy Probabilistic Programming Language for Model Composition and Fitting - Published in JOSS (2021)
Generative DAGs as an Interface Into Probabilistic Programming with the R Package causact
Generative DAGs as an Interface Into Probabilistic Programming with the R Package causact - Published in JOSS (2022)
bayes-toolbox
bayes-toolbox: A Python package for Bayesian statistics - Published in JOSS (2023)
GPJax
GPJax: A Gaussian Process Framework in JAX - Published in JOSS (2022)
RxInfer
RxInfer: A Julia package for reactive real-time Bayesian inference - Published in JOSS (2023)
genparticlefilters.jl
Building blocks for simple and advanced particle filtering in Gen.
prob-epi
Course materials of "Bayesian Modelling and Probabilistic Programming with Numpyro, and Deep Generative Surrogates for Epidemiology"
pyprobables
Probabilistic data structures in python http://pyprobables.readthedocs.io/en/latest/index.html
forneylab.jl
Julia package for automatically generating Bayesian inference algorithms through message passing on Forney-style factor graphs.
symbolicai
A neurosymbolic perspective on LLMs
markovjunior
Probabilistic language based on pattern matching and constraint propagation, 153 examples
DiffEqBayes
Extension functionality which uses Stan.jl, DynamicHMC.jl, and Turing.jl to estimate the parameters to differential equations and perform Bayesian probabilistic scientific machine learning
https://github.com/juliagaussianprocesses/abstractgps.jl
Abstract types and methods for Gaussian Processes.
https://github.com/pyro-ppl/numpyro
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
mcx
Express & compile probabilistic programs for performant inference on CPU & GPU. Powered by JAX.
https://github.com/dharasim/simpleprobabilisticprograms.jl
Simple implementation of probabilistic programs for the Julia programming language
https://github.com/alexhallam/tablespoon
🥄✨Time-series Benchmark methods that are Simple and Probabilistic
https://github.com/google-research/recsim_ng
RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems
https://github.com/isms/mcmc-rs
A Rust library implementing various MCMC diagnostics and utilities, such as Gelman Rubin potential scale reduction factor (R hat), effective sample size, chain splitting, and others.
https://github.com/baggepinnen/turing2montecarlomeasurements.jl
Interface between Turing.jl and MonteCarloMeasurements.jl
https://github.com/chalk-lab/mcmctempering.jl
Implementations of parallel tempering algorithms to augment samplers with tempering capabilities
NonparametricVI
Particle-based and nonparametric variational methods for approximate Bayesian inference and Probabilistic Programming
https://github.com/jiayaobo/fenbux
A Simple Statistical Distribution Library in JAX
https://github.com/barrust/count-min-sketch
Count-Min Sketch Implementation in C
ReactiveMP
High-performance reactive message-passing based Bayesian inference engine
https://github.com/cbg-ethz/shm
Deep hierarchical models combined with Markov random fields.
genjax
Probabilistic programming with programmable inference for parallel accelerators.
https://github.com/daeh/computed-appraisals
Computed Appraisals Model. Code and data for the 2023 paper, "Emotion prediction as computation over a generative theory of mind"