The need for either priors or labelled data So my view is that unsupervised representation learning is really hopeless without either: meaningful, strong priors or assumptions about the behaviourally relevant variables, or the decision problems we want to use our representations for, or at least some labelled data to inform the training procedure about behaviourally relevant aspects, i.e.