  Universal differential equations (UDEs) leverage the respective advantages of
mechanistic models and artificial neural networks and combine them into one
dynamic model. However, these hybrid models can suffer from unrealistic
solutions, such as negative values for biochemical quantities. We present
non-negative UDE (nUDEs), a constrained UDE variant that guarantees
non-negative values. Furthermore, we explore regularisation techniques to
improve generalisation and interpretability of UDEs.
