SimbaML is an all-in-one framework for integrating prior knowledge of ODE models into the ML process by synthetic data augmentation. It allows for the convenient generation of realistic synthetic data by sparsifying and adding noise. Furthermore, our framework provides customizable pipelines for various ML experiments, such as transfer learning.

This is the code repository for the paper "Optimizing ODE-derived Synthetic Data for Transfer Learning in Dynamical Biological Systems".