arXiv:2609.04329v1 Announce Type: new
Abstract: In this paper, the problem of data-driven discovery of nonlinear ordinary differential equations (ODEs) is recast, and a new interpretable machine learning (ML) method is proposed. The proposed method aims to learn the unknown vector field of nonlinear dynamics without prior knowledge of the system’s physics from only one single state trajectory’s data. The proposed method has two fundamental differences with existing methods: 1) the formulation p