AdamB: Decoupled Bayes by Backprop With Gaussian Scale Mixture Prior
Overfitting of neural networks to training data is one of the most significant problems in machine learning. Bayesian neural networks (BNNs) are known to be robust against overfitting owing to their ability to model parameter uncertainty. Bayes by Backprop (BBB), a simple variational inference appro...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2022-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9874837/ |