Comparison of sigmoid belief nets and Boltzmann machines
	• SBN’s can use a bigger learning rate because they do not have the negative phase (see Neal’s paper). • It is much easier to generate samples from an SBN so we can see what model we learned. • It is easier to interpret the units as hidden causes.			• The Gibbs sampling procedure is much simpler in BM’s. • Gibbs sampling and learning only require communication of binary states in a BM, so its easier to fit into a brain.