Sparse Bayesian Neural Networks: Bridging Model and Parameter Uncertainty through Scalable Variational Inference

Sparse Bayesian Neural Networks: Bridging Model and Parameter Uncertainty through Scalable Variational Inference

Bayesian neural networks (BNNs) have recently regained a significant amount of attention in the deep learning community due to the development of scalable approximate Bayesian inference techniques. There are several advantages of using a Bayesian approach: parameter and prediction uncertainties beco...

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Bibliographic Details
Main Authors: Aliaksandr Hubin, Geir Storvik
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Mathematics
Subjects:
Bayesian neural networks
structural learning
model selection
model averaging
approximate Bayesian inference
predictive uncertainty
Online Access:https://www.mdpi.com/2227-7390/12/6/788

Internet

https://www.mdpi.com/2227-7390/12/6/788

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