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Neural networks can achieve percent-level accuracy in solving complex quantum field equations, outperforming traditional methods in robustness and stability.
Soft gauge fixing stabilizes training and expands the learning rate regime for homogeneous neural networks by penalizing redundant scale imbalances.
