This library implements differentiable SDE solvers that support GPU computation and automatic differentiation for training neural stochastic differential equation models. It provides the sdeint function to numerically integrate SDEs with customizable drift and diffusion functions, enabling applications like learning latent stochastic processes from data. The library is part of the neural differential equations research area within deep learning.