K. Rojek

From symmetry to sparsity: A dual framework of LiSHT and ReXTanh activation functions for deep learning

This paper analyzes the already established Linearly Scaled Hyperbolic Tangent function and proposes ReXTanh, a smooth-sparse hybrid function that provides C 1 continuity while remaining asymmetric, showing that keeping negative magnitudes can outmatch forced sparsity in harder recognition problems.