Easy, minimal interface to the Stan samplers in several languages
BSD-3-CLAUSE License
Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.
Bayesian inference with probabilistic programming.
BridgeStan provides efficient in-memory access through Python, Julia, and R to the methods of a S...
[draft] Agnostic Machine Learning models working on CPUs, GPUs, distributed architecture, etc.
A tool to for optimizing parameters of ordinary differential equation (ODE) models. SBML2Julia tr...
JuliaLang version of "An Introduction to Statistical Learning: With Applications in R"
Write meta graphs quickly
The Julia to Typst interface
Probabilistic programming via source rewriting
Julia implementation of the scikit-learn API https://cstjean.github.io/ScikitLearn.jl/dev/
Bayesian Cognitive Modeling with Turing.jl (Julia Programming Language)
Graphical tools for Bayesian inference and posterior predictive checks
Types and utility functions for summarizing Markov chain Monte Carlo simulations
A benchmarking framework for the Julia language
Bayesian Generalized Linear models using `@formula` syntax.