Non-Negative Universal Differential Equations With Applications in Systems Biology
Quantitative Methods
2024-12-05 v1 Machine Learning
Dynamical Systems
Machine Learning
Abstract
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.
Cite
@article{arxiv.2406.14246,
title = {Non-Negative Universal Differential Equations With Applications in Systems Biology},
author = {Maren Philipps and Antonia Körner and Jakob Vanhoefer and Dilan Pathirana and Jan Hasenauer},
journal= {arXiv preprint arXiv:2406.14246},
year = {2024}
}
Comments
6 pages, This work has been submitted to IFAC for possible publication. Initial submission was March 18, 2024