loopy-belief-propagation

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

Optimized (very fast) stereo matching algorithms in MATLAB and Python. It includes implementations of Block Matching, Dynamic Programming, Semi-Global Matching and Belief Propagation.

Lightweight Rust/Python library for multi-sensor labelled Bernoulli filters - A (mostly automated) rust port of https://github.com/scjrobertson/multisensor-lmb-filters

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

Graph: Representation, Learning, and Inference Methods

A C++ implementation of Loopy Belief Propagation for stereo matching, featuring six alternative message update schedules to analyze convergence behavior and solution quality.

MATLAB implementations of Loopy Belief Propagation (LBP) for stereo matching, featuring Sum-Product, Max-Product and Min-Sum message-passing algorithms for disparity estimation.

Image Denoising Algorithms in MATLAB. It includes implementations of Block Matching, Belief Propagation and ICM (Iterated Conditional Modes).

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

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

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

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.

Evolution of Basic Stereo Matching Algorithms. From Block Matching and Dynamic Programming to Semi-Global Matching and Belief Propagation. Compare the source code to see the improvements.

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

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