284 Open source projects that are alternatives of or similar to LogDensityProblems.jl

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

Implementing MCMC sampling from scratch in R for various Bayesian models

bayesplot R package for plotting Bayesian models

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

An easy-to-use interface for measuring uncertainty and robustness.

An R package and Shiny application to provide API access to the WorldPop Open Population Repository (WOPR)

Probabilistic Inference on Noisy Time Series

Transformations to contrained variables from ℝⁿ.

An unsupervised machine learning algorithm for the segmentation of spatial data sets.

A Java Toolbox for Scalable Probabilistic Machine Learning

🐙 Generalized additive models in Python with a Bayesian twist

DynamicHMC versions of StatisticalRethinking models

An R package to manipulate MCMC samples

Julia package for automatically generating Bayesian inference algorithms through message passing on Forney-style factor graphs.

Notebooks about Bayesian methods for machine learning

Markov chain Monte Carlo solver for lattice spin systems implemented by Julialang

Tools for the symbolic manipulation of PyMC models, Theano, and TensorFlow graphs.

Course on data assimilation (DA)

Hidden Markov models in PyMC3

A didactic Gaussian process package for researchers in Jax.

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 ;)

Multiagent reinforcement learning simulation framework - Undergraduate thesis in Mechatronics Engineering at the University of Brasília

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

Library of composable generative population models which serve as the modeling and inference backend of BayesDB.

A simple probabilistic programming language.

machine learning

Probabilistic reasoning and statistical analysis in TensorFlow

High-quality implementations of standard and SOTA methods on a variety of tasks.

Implementations of the ICML 2017 paper (with Yarin Gal)

🐢 bayesAB: Fast Bayesian Methods for A/B Testing

Exploratory analysis of Bayesian models with Julia

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.

Bayesian Model Averaging for Random and Fixed Effects Meta-Analysis

Implementation of Bayesian Personalized Ranking (BPR) for Multiple Feedback Channels

Learn how to use PyCBC to analyze gravitational-wave data and do parameter inference.

Bayesian Deep Learning: A Survey

A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.

Bindings for Bayesian TidyModels

PyRate is a program to estimate speciation, extinction, and preservation rates from fossil occurrence data using a Bayesian framework.

Bayesian optimization for Python

🔗 Methods for Correlation Analysis

yet another general purpose naive bayesian classifier.

Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. Now almost entirely superseded by the models-by-example repo.

A Latent Dirichlet Allocation implementation in Python.

Bayesian tools for fitting molecular mechanics torsion parameters to quantum chemical data.

MTfit code for Bayesian Moment Tensor Fitting

Bayesian nonparametric models for python

Using neural network to build expressive hierarchical distribution; A variational method to accurately estimate posterior uncertainty; A fast and general method for Bayesian inference. (ICML 2018)

Tutorial on model assessment, model selection and inference after model selection

The Predictive Ecosystem Analyzer (PEcAn) is an integrated ecological bioinformatics toolbox.

[ WSDM '19 ] Sequential Variational Autoencoders for Collaborative Filtering

"What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).

Hierarchical Bayesian modeling of RLDM tasks, using R & Python

Bayesian nowcasting with adjustment for delayed and incomplete reporting to estimate COVID-19 infections in the United States

Tree Approximate Message Passing

An interactive online reading of McElreath's Statistical Rethinking

Bayesian multi-object tracking

Materials of the Nordic Probabilistic AI School 2019.

A general-purpose probabilistic programming system with programmable inference

Scalable sparse Bayesian learning for large CS recovery problems