This project has two parts. In part one, we use markov random field to denoise an image. In Part two, we use similar model for image segmentation.

A high-performance general-purpose MRF MAP solver, heavily exploiting SIMD instructions.

LBP-based segmentation of defocus blur

GammaRay: a graphical interface to GSLib and other geomodeling algorithms. *NEW* in May, 6th: Drift analysis.

Image Crowd Counting Using Convolutional Neural Network and Markov Random Field

Markov random fields with covariates

Image segmentation using the EM algorithm that relies on a GMM for intensities and a MRF model on the labels. Based on "Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm" (Zhang, Y et al.)

A Tutorial on Modeling and Inference in Undirected Graphical Models for Hyperspectral Image Analysis

Conditional Auto-Regressive LASSO in R

A Bayesian framework for Multi-Frame Image Super-Resolution. Based on "Bayesian Image Super-Resolution" (ME Tipping and CM Bishop, NeurIPS 2003)

Framework for event- and frame-based stereo matching using SNNs and MRFs

Expectation Particle Belief Propagation code

Probabilistic machine learning for reconstruction and parametrization of electronic band sturcture from photoemission spectroscopy data

An R package for analysis of Markov Random Fields on 2-dimensional lattices.

Evaluating dependencies among random variables.

A MAP-MRF Framework for Image Denoising

TREC'15 CDS Competition: WSU-IR at TREC 2015 Clinical Decision Support Track: Joint Weighting of Explicit and Latent Medical Query Concepts from Diverse Sources [code]

A package to perform EP inference in a variety of settings

Probabilistic Graphical Models final project