Random fields and Gaussian processes constitute fundamental frameworks in modern probability theory and spatial statistics, providing robust tools for modelling complex dependencies over space and ...

Abstract: Markov random field (MRF) models are a popular tool for vision and image processing. Gaussian MRF models are particularly convenient to work with because they can be implemented using matrix ...

This repository contains MATLAB scripts and a report for simulating and analyzing Gaussian random variables, focusing on their statistical properties such as mean, variance, and probability density ...

Abstract: A conditional multi-target mean and covariance are calculated based on a Gaussian random field approximation of point processes. We derive a particular solution based on a multi-target model ...

We present a novel language identification technique using our recently developed deep-structured conditional random fields (CRFs). The deep-structured CRF is a multi-layer CRF model in which each ...

CATALOG DESCRIPTION: Fundamentals of random variables; mean-squared estimation; limit theorems and convergence; definition of random processes; autocorrelation and stationarity; Gaussian and Poisson ...