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MaLGa Center, DIMA, Universit脿 degli Studi di Genova, Genoa, Italy
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PIKS achieves universal consistency for physics-informed learning, outperforming traditional methods while maintaining analytical tractability.
Generative models can now be rigorously applied to compressed sensing in infinite-dimensional spaces, enabling stable signal recovery with resolution-independent sampling.
