BridgeStan provides efficient in-memory access through Python, Julia, and R to the methods of a Stan model.
BSD-3-CLAUSE License
Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.
A Julia package for Cluster Validity Indices (CVIs).
Performance and data profiles
Computing reachable states of dynamical systems in Julia
This repository holds slides and code for a full Bayesian statistics graduate course.
High-Performance Symbolic Regression in Python and Julia
A statistical toolbox for diffusion processes and stochastic differential equations. Named after ...
Curated decibans of Julia programming language.
Graphical tools for Bayesian inference and posterior predictive checks
A Julia package for Adaptive Resonance Theory (ART) algorithms.
Probabilistic programming via source rewriting
Easy, minimal interface to the Stan samplers in several languages
Bayesian Statistics using Julia and Turing
A benchmarking framework for the Julia language
Generalized Linear Regressions Models (penalized regressions, robust regressions, ...)