Bayesian Neural Networks via MCMC: A Python-Based Tutorial

Bayesian Neural Networks via MCMC: A Python-Based Tutorial

Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain Monte-Carlo (MCMC) sampling methods are used to implement Bayesian inference. In the past few decades, MCMC sampling...

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Bibliographic Details
Main Authors: Rohitash Chandra, Joshua Simmons
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
MCMC
Bayesian deep learning
Bayesian neural networks
Bayesian linear regression
Bayesian inference
Online Access:https://ieeexplore.ieee.org/document/10530647/

Internet

https://ieeexplore.ieee.org/document/10530647/

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