Binary Stochastic Neurons in Tensorflow • /r/MachineLearning

I'm curious if it's possible to use the reparametrization trick to move the stochasticity outside the model, like this: Now that the stochasticity is outside the model, you can just use vanilla stochastic gradient descent in tensorflow. What is interesting about this approach seems to be the many different gradient estimators available, and i'm wondering if these tricks can bleed back into the variational deep learning literature.