264 Open source projects that are alternatives of or similar to Rhat_ess

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.

A collection of Bayesian data analysis recipes using PyMC3

rstanarm R package for Bayesian applied regression modeling

shinystan R package and ShinyStan GUI

A common framework for implementing and using log densities for inference.

How to do Bayesian statistical modelling using numpy and PyMC3

Statistical Rethinking with PyTorch and Pyro

Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.

High-performance Bayesian Data Analysis on the GPU in Clojure

RStan, the R interface to Stan

Bayesian Data Analysis demos for Python

Examples for Bayesian inference using DynamicHMC.jl and related packages.

A Python package for building Bayesian models with TensorFlow or PyTorch

C++ template library for probabilistic programming

A high-level Bayesian analysis API written in Python

Statistical Rethinking course in pymc3

Bayesian Data Analysis demos for R

Bayesian spatial analysis

Solutions of practice problems from the Richard McElreath's "Statistical Rethinking" book.

Material for a Bayesian statistics workshop

Multi-core BUGS for fast Bayesian inference of large hierarchical models

loo R package for approximate leave-one-out cross-validation (LOO-CV) and Pareto smoothed importance sampling (PSIS)

A python module to detect stellar flares using Bayesian model comparison

PyMC3 educational resources

Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code

ParaMonte: Plain Powerful Parallel Monte Carlo and MCMC Library for Python, MATLAB, Fortran, C++, C.

Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.

PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course

Personal project to compare hierarchical linear regression in PyMC3 and PyStan, as presented at http://pydata.org/london2016/schedule/presentation/30/ video: https://www.youtube.com/watch?v=Jb9eklfbDyg

Bayesian inference with probabilistic programming.

Bayesian Coherent Point Drift (BCPD/BCPD++); Source Code Available

Expressions and dataframes with statistical details 📉 📜🔣✅

Deep universal probabilistic programming with Python and PyTorch

ELFI - Engine for Likelihood-Free Inference

A Bayesian Analysis Toolkit in Julia

Collection of probabilistic models and inference algorithms

Separating Normalizing Flows code from Pyro and improving API

Projection predictive variable selection

GPstuff - Gaussian process models for Bayesian analysis

The base NIMBLE package for R

Full Bayesian Inference for Hidden Markov Models

Blang's software development kit

Forecasting 🇫🇷 elections with Bayesian statistics 🥳

Pure julia implementation of Multiple Affine Invariant Sampling for efficient Approximate Bayesian Computation

Probabilistic programming via source rewriting

Simultaneous Localization and Mapping(SLAM) also gives you a way to track the location of a robot in the world in real-time and identify the locations of landmarks such as buildings, trees, rocks, and other world features.

Stanマニュアルの日本語への翻訳プロジェクト

Transformations to contrained variables from ℝⁿ.

Statistical Rethinking (2nd Ed) with Tensorflow Probability

A probabilistic programming language that combines automatic differentiation, automatic marginalization, and automatic conditioning within Monte Carlo methods.

🎓 Uni-Bonn Decision Analysis graduate course, lectures and materials

Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

Bayesian analysis + tidy data + geoms (R package)

👻 Utilities for analyzing Bayesian models and posterior distributions

Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现

Resources to learn more about Machine Learning and Artificial Intelligence

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

Probabilistic reasoning and statistical analysis in TensorFlow

Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch

A probabilistic programming language in TensorFlow. Deep generative models, variational inference.