A machine learning architecture employs two machine learning networks that are joined by a statistical model allowing the imposition of a predetermined statistical model family into a learning process in which the networks translate between and data types. For example, the statistical model may enforce a Gaussian conditional probability between the latent variables in the translation process. In one application, MRI images may be translated into PET images with reduced mode collapse, blurring, or other “averaging” type behaviors.