optimization based approaches where we're saying that the meta parameters serve as a prior and we talked about how one form of prior knowledge is is initialization for fine-tuning can we make this a bit more formal and actually better characterize what's work sort of prior that is it mammal is imposing on the learning process and to do so we're going to look at Bayesian meta learning approaches that use graphical models so this is a kind of a graphical model similar to the one that Sergei showed before where Phii is the top specific