work has done is to show that you can actually do that with really good performance in an unsupervised way so now I have two embedding space and then you are lying them without any training signal so the way that is done is actually basically just using the principle of marginal matching so you would similarly apply so basically you your rotation each of each possible rotation basically specify a mapping and then you're going to say after the mapping my marginal distributions to match and then they just train that with