no biases in your system by selecting the right architectures loss functions and etc and you can actually get to a certain level of success with this yeah so they expect this this one basically says for an arbitrary data porn in its it's just a generalized version of the cycle consistency thing so for any of the data porn a if I draw samples for my approximate conditional distribution and then I translate that B back to a using my approximate once the the distribution that induce should be similar to if you do it with the real-world one and what