6109 Open source projects that are alternatives of or similar to Dbda Python

Bayesian Data Analysis demos for Python

High-performance Bayesian Data Analysis on the GPU in Clojure

A collection of Bayesian data analysis recipes using PyMC3

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

How to do Bayesian statistical modelling using numpy and PyMC3

RStan, the R interface to Stan

Make a sweet giant triangle confusogram (GTC) plot

shinystan R package and ShinyStan GUI

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

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

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

Bayesian Data Analysis demos for R

NIPS 2017: ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching

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Fast and Easy Infinite Neural Networks in Python

Generalized linear mixed-effect model in Python

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

Scalable inference for a generative model of astronomical images

Simulation-based inference in PyTorch

Boltzmann Machines in TensorFlow with examples

A Bayesian Analysis Toolkit in Julia

Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara

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

The base NIMBLE package for R

Python package for learning the graphical structure of Bayesian networks, parameter learning, inference and sampling methods.

🎓 Educational application of Hidden Markov Model to Autonomous Driving 🚕🚙🚗

PyMC3 educational resources

Bayesian Evolutionary Analysis by Sampling Trees

Collection of probabilistic models and inference algorithms

Bayesian Deep Learning with Stochastic Gradient MCMC Methods

Code for "A-NICE-MC: Adversarial Training for MCMC"

Statistical Rethinking (2nd Ed) with Tensorflow Probability

Python package for computing the Curie depth from the magnetic anomaly

A statistical toolbox for diffusion processes and stochastic differential equations. Named after the Brownian Bridge.

Single-cell copy number calling and event history reconstruction.

Nested Sampling post-processing and plotting

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

Bayesian inference with probabilistic programming.

Distributed Bayesian Entity Resolution in Apache Spark

Gathers Machine learning models using pure Numpy to cover feed-forward, RNN, CNN, clustering, MCMC, timeseries, tree-based, and so much more!

Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath

A repository to keep track of all the code that I end up writing for my blog posts.

Collection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.

Fast & scalable MCMC for all your exoplanet needs!

A web interface for exploring PyMC3 traces

Blang's software development kit

GPstuff - Gaussian process models for Bayesian analysis

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

Material for a workshop on Bayesian stats with R

Stanマニュアルの日本語への翻訳プロジェクト

Sequential Monte Carlo algorithm for approximation of posterior distributions.

Full Bayesian Inference for Hidden Markov Models

Rank-normalization, folding, and localization: An improved R-hat for assessing convergence of MCMC

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.

Graphical tools for analyzing Markov Chain Monte Carlo simulations from Bayesian inference

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

rstanarm R package for Bayesian applied regression modeling

Variational autoencoders for collaborative filtering