Probabilistic Graphical Model
GPTKB entity
Statements (50)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
statistical analysis
graphical model |
| gptkbp:application |
computer vision
natural language processing robotics speech recognition bioinformatics |
| gptkbp:conference |
gptkb:AAAI
gptkb:UAI gptkb:NIPS gptkb:ICML |
| gptkbp:describes |
conditional dependence structure
|
| gptkbp:enables |
inference
learning prediction |
| gptkbp:field |
gptkb:artificial_intelligence
gptkb:machine_learning statistics |
| gptkbp:hasProperty |
scalable to large datasets
compact representation of joint distributions interpretable structure supports missing data supports uncertainty quantification |
| https://www.w3.org/2000/01/rdf-schema#label |
Probabilistic Graphical Model
|
| gptkbp:includes |
gptkb:Markov_random_field
Boltzmann machine factor graph |
| gptkbp:notableBook |
gptkb:Probabilistic_Graphical_Models:_Principles_and_Techniques
gptkb:Daphne_Koller gptkb:Nir_Friedman |
| gptkbp:notableContributor |
gptkb:Judea_Pearl
gptkb:Daphne_Koller gptkb:Michael_I._Jordan |
| gptkbp:originatedIn |
1980s
|
| gptkbp:publishedIn |
gptkb:Journal_of_Machine_Learning_Research
gptkb:Machine_Learning_Journal |
| gptkbp:relatedTo |
Markov chain
causal inference variational inference belief propagation parameter learning expectation-maximization algorithm latent variable model structure learning graphical lasso |
| gptkbp:represents |
random variables
probabilistic relationships |
| gptkbp:uses |
graph theory
|
| gptkbp:bfsParent |
gptkb:Graphical_Models
|
| gptkbp:bfsLayer |
7
|