Machine Learning, Variational Inference, Bayesian Statistics, Artificial Intelligence.
transitioning to the next sample depends only on the current sample and not on the previous history. This helps us reach a “stationary” distribution over samples, i.e. when we run the chain long enough, the probability P(0 < z < 1 | x)_{n} at iteration n and P(0 < z < 1 | x)_{m} at iteration m