MCO-PDE trains per-dataset neural surrogates, applies soft-competitive weighting for consensus coefficients, and uses a genetic algorithm to identify shared PDE structures from multi-source data.
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Joint discovery of governing partial differential equations from multi-source datasets by competitive optimization
MCO-PDE trains per-dataset neural surrogates, applies soft-competitive weighting for consensus coefficients, and uses a genetic algorithm to identify shared PDE structures from multi-source data.