AWhat changed
Combined positive identity responses with a negative saturating exponential branch to study activation centering, bias-shift effects and deep-network optimization.
Scientific scope
Combined positive identity responses with a negative saturating exponential branch to study activation centering, bias-shift effects and deep-network optimization. General image-learning method despite author institute name; not a biological result. Inherits rectifiers, leaky/PReLU and centering/natural-gradient ideas. Conditional bias-shift analysis and empirical classification gains do not prove that all gradients avoid vanishing or every task benefits; exact zero means are not guaranteed.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. General image-learning method despite author institute name; not a biological result. Inherits rectifiers, leaky/PReLU and centering/natural-gradient ideas. Conditional bias-shift analysis and empirical classification gains do not prove that all gradients avoid vanishing or every task benefits; exact zero means are not guaranteed.
Contributors
- Source-listed authors and technical contributors · SCIENCE: Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
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