Especially, When factorizing multivariate densities into a product of marginal distributions and bivariate copula functions (called as vines) Each of these factors corresponds to one of the building blocks that are assumed either constant or varying across different learning domains applicable to DA, TL and mtLEspecially, when factorizing multivariate densities into a product of marginal distributions and bivariate copula functions (called as vines). Each of these factors corresponds to one of the building blocks that are assumed either constant or varying across different learning domains. → applicable to DA, TL and MTL!