Statements (50)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
probabilistic graphical model
|
| gptkbp:alsoKnownAs |
Markov random fields
|
| gptkbp:application |
natural language processing
statistical inference image segmentation spatial data analysis |
| gptkbp:canLearnMove |
maximum likelihood estimation
contrastive divergence pseudo-likelihood estimation |
| gptkbp:characterizedBy |
graph
|
| gptkbp:component |
edges
nodes cliques potential functions |
| gptkbp:contrastsWith |
directed graphical models
|
| gptkbp:describedBy |
gptkb:statistical_mechanics
|
| gptkbp:feature |
gptkb:Markov_property
conditional independence clique potentials |
| gptkbp:field |
gptkb:artificial_intelligence
data science robotics speech recognition statistics bioinformatics pattern recognition econometrics network science spatial epidemiology |
| gptkbp:hasModel |
joint probability distribution
|
| https://www.w3.org/2000/01/rdf-schema#label |
Markov networks
|
| gptkbp:inferenceMethod |
gptkb:Gibbs_sampling
belief propagation mean field approximation |
| gptkbp:namedAfter |
gptkb:Andrey_Markov
|
| gptkbp:property |
global Markov property
local Markov property pairwise Markov property undirected edges |
| gptkbp:relatedTo |
gptkb:Ising_model
gptkb:Gibbs_distribution gptkb:Conditional_Random_Fields gptkb:Bayesian_networks |
| gptkbp:usedIn |
gptkb:machine_learning
computer vision spatial statistics image processing statistical physics |
| gptkbp:bfsParent |
gptkb:Bayesian_networks
|
| gptkbp:bfsLayer |
6
|