Bayesian neural networks

URI: https://gptkb.org/entity/Bayesian_neural_networks

GPTKB entity

Statements (59)

Predicate	Object
gptkbp:instance_of	gptkb:Statistician gptkb:neural_networks
gptkbp:analyzes	probability distributions
gptkbp:based_on	Bayesian inference
gptkbp:benefits	deep learning models frequentist methods
gptkbp:can_be_used_in	time series analysis active learning transfer learning anomaly detection semi-supervised learning
gptkbp:can_handle	small datasets noisy data
gptkbp:challenges	computational complexity model interpretability hyperparameter optimization
gptkbp:developed_by	gptkb:Bayesians
gptkbp:enables	robust predictions
gptkbp:enhances	decision making
gptkbp:facilitates	model selection
https://www.w3.org/2000/01/rdf-schema#label	Bayesian neural networks
gptkbp:improves	generalization performance
gptkbp:integrates_with	prior knowledge
gptkbp:is_applied_in	gptkb:robotics financial forecasting natural language processing medical diagnosis
gptkbp:is_compared_to	traditional neural networks
gptkbp:is_evaluated_by	cross-validation posterior predictive checks Bayesian model selection
gptkbp:is_implemented_in	gptkb:Tensor_Flow gptkb:Pyro gptkb:Edward gptkb:Py_Torch gptkb:Tensor_Flow_Probability
gptkbp:is_popular_in	gptkb:academic_research machine learning community
gptkbp:is_related_to	gptkb:machine_learning deep learning ensemble methods probabilistic programming Gaussian processes
gptkbp:is_used_by	data scientists machine learning engineers
gptkbp:provides	model uncertainty
gptkbp:requires	hyperparameter tuning more computational resources expertise in Bayesian statistics
gptkbp:training	variational inference Markov Chain Monte Carlo (MCMC)
gptkbp:used_for	classification tasks regression tasks uncertainty estimation
gptkbp:utilizes	prior distributions posterior distributions
gptkbp:bfsParent	gptkb:Auto-Encoding_Variational_Bayes gptkb:Pyro
gptkbp:bfsLayer	5