and probability, a Markov random field (MRF), Markov network or undirected graphical model is a set of random variables having a Markov property described...
19 KB (2,777 words) - 08:08, 29 April 2024
In probability theory, a Markov model is a stochastic model used to model pseudo-randomly changing systems. It is assumed that future states depend only...
10 KB (1,175 words) - 07:55, 18 July 2024
term Markov assumption is used to describe a model where the Markov property is assumed to hold, such as a hidden Markov model. A Markov random field extends...
9 KB (1,211 words) - 07:29, 3 April 2024
hidden Markov random field is a generalization of a hidden Markov model. Instead of having an underlying Markov chain, hidden Markov random fields have...
2 KB (315 words) - 18:10, 13 January 2021
takes on random values over a space of functions (see Feynman integral). Several kinds of random fields exist, among them the Markov random field (MRF),...
8 KB (1,128 words) - 19:54, 12 July 2024
in 1988. A Markov blanket can be constituted by a set of Markov chains. A Markov blanket of a random variable Y {\displaystyle Y} in a random variable set...
4 KB (538 words) - 06:28, 15 May 2024
In statistics, a Gaussian random field (GRF) is a random field involving Gaussian probability density functions of the variables. A one-dimensional GRF...
2 KB (262 words) - 03:25, 13 March 2024
rare failure region.[citation needed] Markov chain Monte Carlo methods create samples from a continuous random variable, with probability density proportional...
29 KB (3,092 words) - 06:30, 27 August 2024
geostatistics Markov chain mixing time Markov chain tree theorem Markov decision process Markov information source Markov odometer Markov operator Markov random field...
93 KB (12,484 words) - 09:37, 15 August 2024
A hidden Markov model (HMM) is a Markov model in which the observations are dependent on a latent (or "hidden") Markov process (referred to as X {\displaystyle...
51 KB (6,744 words) - 15:08, 26 August 2024