What can we do if there are too many parameters for a grid to be feasible?
	• The number of grid points is exponential in the number of parameters. – So we cannot deal with more than a few parameters using a grid. • If there is enough data to make most parameter vectors very unlikely, only need a tiny fraction of the grid points make a significant contribution to the predictions. – Maybe we can just evaluate this tiny fraction • It might be good enough to just sample weight vectors according to their posterior probabilities.
				Sample weight vectors with this probability