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University of Bristol, RIKEN AIP, University of Tokyo &
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ZF2ST achieves strong testing power for detecting distributional differences while maintaining rigorous statistical validity, outperforming traditional methods.
Takeuchi's Information Criterion (TIC) accurately predicts DNN generalization gaps, but only when models operate near the Neural Tangent Kernel (NTK) regime.
