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.
The official implementation of CROMP (Constrained Regression with Ordered and Margin-sensitive Parameters). CROMP allows user-defined order among the coefficients, user-defined minimum margins (i.e., percentage gaps) between them, and user-defined lower and upper bounds for each coefficient. In addition, CROMP also allows coefficients without any order or margin restrictions.
