bayes-by-backprop
1 Appendix 1 Bayes-by-backprop The Bayesian posterior neural network distribution P (w |D) is approximated
In Algorithm 1 we give the full clustering algorithm used for each of the T fixing iterations. In Figure 1 we show how the layers' In Figure 2 we show the impact of increasing the regularisation strength.
Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (1.00)
To all reviewers
We would like to sincerely thank you for your important ideas and constructive comments. It is not related to the deep learning domain. We will clearly state these contributions in the paper. As you suggest, we will define B2N, RAI, and GGT in the paper. Optimizing for a specific loss hinders other objectives, e.g., accuracy and calibration.