Scientific Machine Learning (SciML) is the branch of scientific computing that combines domain-aware and interpretable models with powerful machine learning techniques. The Julia language has been a key enabler of this burgeoning field, thanks to its unique SciML ecosystem. In this talk, we will present a contribution in this direction: an easy and flexible implementation of generative latent differential equations models.