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Function space flow matching stumbles when treating continuous fields like flat Euclidean vectors, but pairing endpoints via Hilbert Sinkhorn Divergence unlocks provably discretization-invariant generation across complex PDE systems.
Calibration, out-of-distribution detection, and concept shift in graph networks can all be solved by a single representation鈥攃oupling graph Fourier transforms with polynomial chaos beats specialized baselines across all three tasks without post-hoc tuning.
