Identifiability Challenges in Sparse Linear Ordinary Differential Equations

ArXi:2506.09816v3 Announce Type: replace Dynamical systems modeling is a core pillar of scientific inquiry across natural and life sciences. Increasingly, dynamical system models are learned from data, rendering identifiability a paramount concept. For systems that are not identifiable from data, no guarantees can be given about their behavior under new conditions and inputs, or about possible control mechanisms to steer the system.