Statements (28)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
Markov chain
sampling algorithm |
| gptkbp:application |
gptkb:Bayesian_networks
image processing topic modeling hierarchical models |
| gptkbp:category |
gptkb:Monte_Carlo_methods
gptkb:Computational_statistics Stochastic simulation |
| gptkbp:convergesTo |
target joint distribution
|
| https://www.w3.org/2000/01/rdf-schema#label |
Gibbs Sampling
|
| gptkbp:introducedIn |
1984
|
| gptkbp:limitation |
slow mixing for highly correlated variables
|
| gptkbp:namedAfter |
gptkb:Josiah_Willard_Gibbs
|
| gptkbp:relatedTo |
gptkb:Metropolis-Hastings_algorithm
Markov chain conditional probability |
| gptkbp:requires |
full conditional distributions
|
| gptkbp:step |
sample from conditional distribution
update one variable at a time |
| gptkbp:supportsAlgorithm |
iterative
|
| gptkbp:usedFor |
generating samples from a multivariate probability distribution
|
| gptkbp:usedIn |
gptkb:machine_learning
Bayesian statistics statistical inference |
| gptkbp:bfsParent |
gptkb:Contrastive_Divergence
gptkb:Bayesian_Learning |
| gptkbp:bfsLayer |
7
|