Meta-Inverse Physics-Informed Neural Networks for High-Dimensional Ordinary Differential Equations

ArXi:2605.03511v1 Announce Type: new Solving inverse problems in dynamical systems governed by high-dimensional coupled ordinary differential equations (ODEs) is a ubiquitous challenge in scientific machine learning. In many real-world applications, researchers seek to uncover unknown parameters or model unknown dynamics even as the underlying physics is only partially characterized, and observations are sparse and limited to specific measurable channels.