Deep Bayesian Neural Networks. – Stefano Cosentino – Medium

Conventional neural networks aren't well designed to model the uncertainty associated with the predictions they make. For that, one way is to go full Bayesian. What are we trying to do? Any deep network has parameters, often in the form of weights (w_1, w_2, …) and biases (b_1,b_2, …). The conventional (non-Bayesian) way is to learn only the optimal values via maximum likelihood estimation.