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gptkbp:instanceOf
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Machine Learning Paradigm
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gptkbp:advantage
|
Flexible Modeling
Incorporates Prior Knowledge
Quantifies Uncertainty
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gptkbp:appliesTo
|
gptkb:Computer_Vision
gptkb:robot
gptkb:Bioinformatics
gptkb:Natural_Language_Processing
Econometrics
|
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gptkbp:basedOn
|
gptkb:Bayes'_Theorem
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gptkbp:challenge
|
Scalability
Computational Complexity
Approximate Inference
Choice of Priors
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gptkbp:contrastsWith
|
Frequentist Learning
|
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gptkbp:enables
|
Prediction
Parameter Estimation
Model Selection
|
|
gptkbp:focusesOn
|
Probabilistic Inference
Updating Beliefs
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|
https://www.w3.org/2000/01/rdf-schema#label
|
Bayesian Learning
|
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gptkbp:notableFigure
|
gptkb:Pierre-Simon_Laplace
gptkb:Thomas_Bayes
|
|
gptkbp:relatedTo
|
Bayesian Inference
Frequentist Learning
|
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gptkbp:usedIn
|
gptkb:Machine_Learning
gptkb:artificial_intelligence
Statistics
|
|
gptkbp:uses
|
gptkb:Markov_Chain_Monte_Carlo
gptkb:Hidden_Markov_Models
gptkb:Bayesian_Networks
gptkb:Bayesian_Linear_Regression
gptkb:Bayesian_Neural_Networks
gptkb:Bayesian_Optimization
gptkb:Dirichlet_Processes
gptkb:Expectation-Maximization
gptkb:Gibbs_Sampling
gptkb:Laplace_Approximation
gptkb:Variational_Inference
Gaussian Processes
Evidence
Likelihood Function
Conjugate Priors
Hierarchical Models
Nonparametric Methods
Posterior Predictive Distribution
Posterior Probability
Prior Probability
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gptkbp:bfsParent
|
gptkb:Max_Welling
|
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gptkbp:bfsLayer
|
6
|