Approximate inference
		• What if we use an approximation to the posterior distribution over hidden configurations? – e.g. assume the posterior factorizes into a product of distributions for each separate hidden cause. • If we use the approximation for learning, there is no guarantee that learning will increase the probability that the model would generate the observed data. • But there is a different function, called “variational free energy” that is guaranteed to improve: