Bayesian Generalized Linear models using `@formula` syntax.

Probabilistic Programming with Gaussian processes in Julia

Probabilistic Numerics in Python.

Code accompanying the NeurIPS 2021 Paper: A Probabilistic State Space Model for Joint Inference from Differential Equations and Data (Schmidt, Krämer, Hennig)

Source files for the book "Bayesian Workflow Using Stan"

Python Package for Bayesian Quantile Matching Estimation

Implementations of kernel-based goodness-of-fit tests.

A repository for collating all the resources such as articles, blogs, papers, and books related to Bayesian Statistics.

A collection of commonly used datasets as benchmarks for density estimation

Develop tools for ensemble Kalman filter

Statistical Rethinking course winter 2022

Simulation-based inference toolkit

BlackBoxOptimizationBenchmarking

Supplementary code for paper "Bayesian workflow for disease transmission model".

Database with posteriors of interest for Bayesian inference

Lecture Notes on Statistical Inference

Bayesian Statistics using Julia and Turing

Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.

Projects of the KTH DD2420 - Probabilistic Graphical Models course.

"Probabilistic Machine Learning" - a book series by Kevin Murphy

WAIC and PSIS model comparison methods as explained in Statistical Rethinking.

Stan.jl illustrates the usage of the 'single method' packages, e.g. StanSample, StanOptimize, etc.

Repo for code from the SBC paper

Multi-language suite for analyzing calibration of probabilistic predictive models.

Specifying, fitting, and evaluating statistical models in Julia

Probabilistic numerical finite differences. Compute finite difference weights and differentiation matrices on scattered data sites and with out-of-the-box uncertainty quantification.