Generating from a learned model
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	• The inputs from the earlier states of the visible units create dynamic biases for the hidden and current visible units. • Perform alternating Gibbs sampling for a few iterations between the hidden units and the current visible units. – This picks new hidden and visible states that are compatible with each other and with the recent history.
				t-2       t-1        t