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gptkbp:instanceOf
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Machine Learning Method
Neural Network Model
|
|
gptkbp:advantage
|
Complex Implementation
High Computational Cost
Difficult to Scale
Quantifies Model Uncertainty
Reduces Overfitting
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gptkbp:appliesTo
|
gptkb:Unsupervised_Learning
Supervised Learning
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|
gptkbp:canBeTrainedWith
|
gptkb:Markov_Chain_Monte_Carlo
gptkb:Laplace_Approximation
gptkb:Variational_Inference
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gptkbp:estimatedCost
|
Posterior Distribution
|
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gptkbp:extendsTo
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gptkb:Artificial_Neural_Networks
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gptkbp:firstDescribed
|
1990s
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gptkbp:handles
|
Uncertainty
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gptkbp:hasComponent
|
Posterior Predictive Distribution
Prior over Weights
Weights as Distributions
|
|
https://www.w3.org/2000/01/rdf-schema#label
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Bayesian Neural Networks
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gptkbp:implementedIn
|
gptkb:Edward
gptkb:TensorFlow_Probability
gptkb:JAX
gptkb:Pyro
gptkb:Stan
PyMC3
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gptkbp:proposedBy
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gptkb:Radford_M._Neal
David J.C. MacKay
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gptkbp:provides
|
Predictive Uncertainty
|
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gptkbp:relatedTo
|
gptkb:Probabilistic_Graphical_Models
Gaussian Processes
Deep Learning
Ensemble Methods
Dropout Regularization
|
|
gptkbp:studiedIn
|
Uncertainty Quantification
Bayesian Deep Learning
Probabilistic Machine Learning
|
|
gptkbp:usedIn
|
gptkb:Computer_Vision
gptkb:robot
gptkb:Natural_Language_Processing
gptkb:Reinforcement_Learning
Medical Diagnosis
Regression
Classification
Time Series Forecasting
Active Learning
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gptkbp:uses
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Bayesian Inference
Likelihood Function
Prior Distribution
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gptkbp:bfsParent
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gptkb:Bayesian_Learning
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gptkbp:bfsLayer
|
7
|