Factor graphs and loopy belief propagation implemented in Python

Overview and implementation of Belief Propagation and Loopy Belief Propagation algorithms: sum-product, max-product, max-sum

Matlab implementations of various multi-sensor labelled multi-Bernoulli filters

The FactorGraph package provides the set of different functions to perform inference over the factor graph with continuous or discrete random variables using the belief propagation algorithm.

Disparity calculation using Loopy Belief Propagation.

Implementation of the Belief Propagation Side Channel Attack

Stochastic Triangular Mesh (STM) Mapping — an online dense mapping technique for mobile robots.

Graph: Representation, Learning, and Inference Methods

An implementation of loopy belief propagation for binary image denoising. Both sequential and parallel updates are implemented.

Matlab implementation of Loopy Belief Propagation algorithm for foreground-background distinction on an image.

Implementation of the loopy belief propagation for denoising and inpainting images.

Probabilistic modeling through Bayesian inference using PyStan with demonstrative case study experiments from Christopher Bishop's Model-based Machine Learning.

Denoise a given image using Loopy Belief Propagation

stereo matching using pgm inference methods

Expectation Maximisation, Variational Bayes, ARD, Loopy Belief Propagation, Gaussian Process Regression

A C++ implementation of Loopy Belief Propagation for stereo matching. It uses the "min-sum" variation of the algorithm and the "Accelerated" (Right-Left-Down-Up pass) message update schedule.

Playground for some learning algorithms on CPU & GPU

A C++ implementation of Loopy Belief Propagation for image denoising. It uses the "min-sum" variation of the algorithm and the "Accelerated" (Right-Left-Down-Up pass) message update schedule.