AINeutralarXiv – CS AI · 10h ago6/10
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Normalization Equivariance for Arbitrary Backbones, with Application to Image Denoising
Researchers present a parameter-free wrapper method (WNE) that enforces Normalization Equivariance—robustness to brightness and contrast shifts—around any neural network backbone without architectural constraints. The approach characterizes NE as a normalize-process-denormalize factorization, enabling compatibility with modern components like transformers and attention mechanisms while avoiding the 1.6x computational overhead of existing methods.