159 Open source projects that are alternatives of or similar to Blackjax

Efficient, lightweight variational inference and approximation bounds

Estimating effective elastic thickness of the lithosphere

solution of exercises of the book "probabilistic robotics"

nway -- Bayesian cross-matching of astronomical catalogues

R-package for interpretable nonparametric modeling of longitudinal data using additive Gaussian processes. Contains functionality for inferring covariate effects and assessing covariate relevances. Various models can be specified using a convenient formula syntax.

Bayesian Data Analysis demos for Python

Forecasting 🇫🇷 elections with Bayesian statistics 🥳

A resource list for causality in statistics, data science and physics

Probabilistic question-asking system: the program asks, the users answer. The minimal goal of the program is to identify what the user needs (a target), even if the user is not aware of the existence of such a thing/product/service.

How to do Bayesian statistical modelling using numpy and PyMC3

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

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

A python module to detect stellar flares using Bayesian model comparison

nessai: Nested Sampling with Artificial Intelligence

PyMC3 educational resources

Full Bayesian Inference for Hidden Markov Models

Resources to learn more about Machine Learning and Artificial Intelligence

Helper functions for brmsfit objects (DEPRECATED)

Distributed Bayesian Entity Resolution in Apache Spark

Sequential Monte Carlo algorithm for approximation of posterior distributions.

Solve and estimate Dynamic Stochastic General Equilibrium models (including the New York Fed DSGE)

Generation of Synthetic Populations Library

Python package for computing the Curie depth from the magnetic anomaly

Infer the gender of an individual based on their name.

Bayesian Data Analysis demos for R

High-performance Bayesian Data Analysis on the GPU in Clojure

Probabilistic Programming with Gaussian processes in Julia

ggplot2 extension for plotting distributions

rstanarm R package for Bayesian applied regression modeling

Deep universal probabilistic programming with Python and PyTorch

The Microbiome Interpretable Temporal Rule Engine

brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan

Material for AMLD 2020 workshop "Bayesian Inference: embracing uncertainty"

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

Sleek implementations of the ZigZag, Boomerang and other assorted piecewise deterministic Markov processes for Markov Chain Monte Carlo including Sticky PDMPs for variable selection

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

Particle filtering and sequential parameter inference in Python

Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.

Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)

RStan, the R interface to Stan

Benchmarks of Bayesian Nonparametric models in Turing and other PPLs

Diffusive Nested Sampling

Noisy network measurement with stan

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

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

A high-level Bayesian analysis API written in Python

Machine Learning - accelerated Bayesian inference

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

Natural Gradient, Variational Inference

C++ template library for probabilistic programming

Data-driven Network-based Bayesian Inference of Drivers

A collection of Bayesian data analysis recipes using PyMC3

Implementation of normalising flows and constrained random variable transformations

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

Variational autoencoders for collaborative filtering

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

A Python library that helps data scientists to infer causation rather than observing correlation.

This contains a number of IP[y]: Notebooks that hopefully give a light to areas of bayesian machine learning.

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

The bookdown version lives here: https://bookdown.org/content/3890