Machine Learning, Statistics, Monte Carlo, Deep Learning.
becomes as similar as possible to p(z). In a neural network, the latent variables z are the weights w, hence we can write: The ‘distance’ between these two distributions is estimated by the Kullback-Leibler (KL) divergence which is calculated as follows: So, we must do nothing more than minimising