Wanfeng Lu

Interpretable Functional Koopman Learning with Non-Markovian Closure for Spatiotemporal Systems

Precise prediction of spatiotemporal dynamics over predictive horizons is constrained by the computational cost of high-fidelity solvers and the sparsity, noise, and irregularity of data. We introduce MERLIN, a Koopman-based framework that lifts dynamics to the evolution of learned *observation func…