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SORT shifts the focus from brittle term selection to adaptive basis design, enabling more robust and accurate equation discovery from noisy data.
Spectral learning faces a fundamental noise threshold that can destabilize coefficient estimates, challenging the reliability of functional recovery from noisy data.
