Normalizing Flows are generative models which produce tractable distributions where both
sampling and density evaluation can be efficient and exact. The goal of this survey article is …

The adjoint sensitivity method scalably computes gradients of solutions to ordinary
differential equations. We generalize this method to stochastic differential equations …

We derive reverse-mode (or adjoint) automatic differentiation for solutions of stochastic
differential equations (SDEs), allowing time-efficient and constant-memory computation of …