On a two-input nuclear binding energy network, the paper validates ANNFT predictions for variance, kurtosis, and an optimal depth-to-width ratio r*=0.034 under SGD, while adaptive optimizers obscure criticality.
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Criticality analysis of nuclear binding energy neural networks
On a two-input nuclear binding energy network, the paper validates ANNFT predictions for variance, kurtosis, and an optimal depth-to-width ratio r*=0.034 under SGD, while adaptive optimizers obscure criticality.