Understanding how to update beliefs from evidence is a foundational skill in statistics and machine learning. This project gives you a practical beginner workflow where you can: specify prior beliefs ...

In this tutorial, we will train a LeNet classifier on the MNIST dataset using Monte-Carlo Dropout (MC Dropout), a computationally efficient Bayesian approximation method. To estimate the predictive ...

Abstract: The Bayesian neural network (BNN) represents model parameters with probability distributions to introduce uncertainty during learning. The variational Bayesian learning approach prevents ...