so that we used to think that the VA was using the KL divergence and got blurry samples and gowns were using the reverse KL divergence and got sharp samples but now that we're able to do both divergences with gans we see that we get sharp samples both ways my interpretation this is that it is the approximation strategy of using supervised learning to estimate the density ratio that leads to the samples being very sharp and that something about the variational bound is what leads to the samples for the VA e being blurry there's one other