Statements (57)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:Statistician
|
| gptkbp:challenges |
hyperparameter tuning
computational complexity convergence diagnostics model selection issues |
| gptkbp:developed_by |
gptkb:David_Blackwell
gptkb:David_M._Blei gptkb:Zoubin_Ghahramani gptkb:Thomas_S._Ferguson Bayesian methods Yee Whye Teh |
| https://www.w3.org/2000/01/rdf-schema#label |
Bayesian nonparametrics
|
| gptkbp:includes |
gptkb:Dirichlet_process
gptkb:Gaussian_process |
| gptkbp:is_applied_in |
regression analysis
clustering survival analysis density estimation |
| gptkbp:is_characterized_by |
flexibility in model structure
infinite-dimensional models nonparametric prior distributions |
| gptkbp:is_criticized_for |
overfitting risks
interpretability issues lack of theoretical guarantees computational demands |
| gptkbp:is_explored_in |
gptkb:academic_conferences
research papers workshops theses |
| gptkbp:is_influenced_by |
nonparametric statistics
|
| gptkbp:is_popular_in |
bioinformatics
data science social sciences econometrics statistical research |
| gptkbp:is_related_to |
Bayesian inference
probability theory latent variable models Bayesian hierarchical models Bayesian model averaging nonparametric Bayesian models |
| gptkbp:is_supported_by |
Variational inference
Approximate Bayesian Computation (ABC) Markov Chain Monte Carlo (MCMC) methods |
| gptkbp:is_taught_in |
tutorials
online courses seminars graduate courses |
| gptkbp:is_used_for |
modeling complex data structures
|
| gptkbp:is_used_in |
gptkb:machine_learning
|
| gptkbp:is_used_to |
test hypotheses
predict outcomes analyze data estimate distributions infer parameters |
| gptkbp:bfsParent |
gptkb:Chinese_Restaurant_Process
|
| gptkbp:bfsLayer |
6
|