Orthogonal Discrepancy Kernels for Learning with Partial Physics
DGX agentarXiv:2606.21199v1 Announce Type: cross Abstract: We introduce a semi-parametric framework for nonlinear system identification, which decouples discrepancy functions from physics-based components. Ort