  We identify an issue in recent approaches to learning-based control that
reformulate systems with uncertain dynamics using a stochastic differential
equation. Specifically, we discuss the approximation that replaces a model with
fixed but uncertain parameters (a source of epistemic uncertainty) with a model
subject to external disturbances modeled as a Brownian motion (corresponding to
aleatoric uncertainty).
