AI RESEARCH
On Data-Driven Koopman Representations of Nonlinear Delay Differential Equations
arXiv CS.LG
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ArXi:2604.03086v1 Announce Type: cross This work establishes a rigorous bridge between infinite-dimensional delay dynamics and finite-dimensional Koopman learning, with explicit and interpretable error guarantees. While Koopman analysis is well-developed for ordinary differential equations (ODEs) and partially for partial differential equations (PDEs), its extension to delay differential equations (DDEs) remains limited due to the infinite-dimensional phase space of DDEs.