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gptkbp:instance_of
|
gptkb:neural_networks
|
|
gptkbp:analyzes
|
Bayesian Model Averaging
|
|
gptkbp:applies_to
|
Uncertainty Estimation
|
|
gptkbp:can_be_combined_with
|
Ensemble Methods
|
|
gptkbp:can_be_used_for
|
gptkb:Regression
Classification
|
|
gptkbp:can_handle
|
Overfitting
|
|
gptkbp:can_provide
|
Confidence Intervals
|
|
gptkbp:challenges
|
gptkb:train
Computational Complexity
Interpret
Scale Up
|
|
gptkbp:developed_by
|
Research Institutions
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Bayesian Neural Networks
|
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gptkbp:improves
|
Generalization
|
|
gptkbp:is_applied_in
|
gptkb:Computer_Vision
gptkb:Natural_Language_Processing
Time Series Forecasting
|
|
gptkbp:is_based_on
|
Bayes' Theorem
|
|
gptkbp:is_beneficial_for
|
gptkb:Risk_Management
Decision Making
Predictive Maintenance
Resource Allocation
Data Imputation
|
|
gptkbp:is_compared_to
|
gptkb:Traditional_Neural_Networks
|
|
gptkbp:is_evaluated_by
|
gptkb:BIC
Cross-Validation
Confusion Matrix
ROC Curve
AIC
Posterior Predictive Checks
|
|
gptkbp:is_explored_in
|
gptkb:Workshops
gptkb:Seminars
Conferences
Theses
Academic Papers
|
|
gptkbp:is_implemented_in
|
gptkb:Tensor_Flow
gptkb:Py_Torch
|
|
gptkbp:is_influenced_by
|
Prior Knowledge
|
|
gptkbp:is_optimized_for
|
gptkb:Hyperparameter_Tuning
|
|
gptkbp:is_popular_in
|
gptkb:scientific_community
|
|
gptkbp:is_recommended_for
|
Small Datasets
|
|
gptkbp:is_related_to
|
Probabilistic Models
|
|
gptkbp:is_supported_by
|
Open Source Libraries
|
|
gptkbp:is_used_for
|
Anomaly Detection
Dimensionality Reduction
Feature Selection
|
|
gptkbp:is_used_in
|
gptkb:stage_adaptation
gptkb:machine_learning
gptkb:Deep_Learning
Generative Models
|
|
gptkbp:provides
|
Model Uncertainty
|
|
gptkbp:requires
|
Prior Distribution
|
|
gptkbp:training
|
gptkb:Markov_Chain_Monte_Carlo
Variational Inference
|
|
gptkbp:uses
|
Bayesian Inference
|
|
gptkbp:bfsParent
|
gptkb:Hugo_Larochelle
|
|
gptkbp:bfsLayer
|
4
|