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Automated symbolic regression can rediscover known HEP functions while achieving high-quality fits, streamlining data analysis in particle physics.
Unlock probabilistic PDE modeling from existing deterministic backbones with a simple retrofitting technique that slashes error by up to 54% and works across diverse architectures.
