you assume that there's no relationship between the training X and the training Y the graphical model assumes that the that there is that the labels Y are dependent on the inputs the the labels Y train are dependent on the inputs X train and the the parameter is Phi okay so let's go through a couple applications this will be quite quick meta learning has been used in a variety of computer vision applications such as image recognition modeling the motion and the pose of humans uses for domain adaptation for example when