Before revision: Neural SDEs combine many of the best qualities of both RNNs and SDEs , and as such are a natural choice for modelling many types of temporal dynamics. They offer memory efficiency , high-capacity function approximation, and strong priors on model space.
After revision: Neural SDEs combine many of the best qualities of both RNNs and SDEs : memory efficient training , high-capacity function approximation, and strong priors on model space.