CR networks maintain accuracy advantages and near-unit gradient tail ratios over ReLU baselines from 5% to 100% training data on Pima Diabetes and SST-5, with the gradient tail ratio proposed as a label-free generalization diagnostic.
Advanced multi-modal neural network for diabetes prediction, 2025.https://www.medrxiv.org/content/10.1101/2025.09.20.25336250v1.full
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Layer-wise Derivative Controlled Networks Achieve Competitive Accuracy and Gradient Stability Across Data Regimes
CR networks maintain accuracy advantages and near-unit gradient tail ratios over ReLU baselines from 5% to 100% training data on Pima Diabetes and SST-5, with the gradient tail ratio proposed as a label-free generalization diagnostic.