Author

Frank Hannig

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Preprint Jul 2026

Rethinking Neural Nonlinearity as Gating

This paper demonstrates that standard activations -- whether piecewise-linear (ReLU, PReLU, Hardtanh) or smooth (SiLU, Sigmoid, Tanh, GELU) -- are in fact instances of a single Threshold Gating (TG) primitive, and proposes a'Minimal Branch Theorem' which relates the minimum number of required branches in the authors' primitive to the trainability of general deep neural networks.

Muhammad Sabih, Frank Hannig, Jürgen Teich · 0 citations