Customized PyTorch implementation of LiSHT (linear scaled hyperbolic tangent) activation function for deep learning, with mean shift and clamping.
Original paper here:
#LiSHT: Non-Parametric Linearly Scaled Hyperbolic Tangent Activation Function for Neural Networks https://arxiv.org/abs/1901.05894
I implemented using Pytorch and wrapped it with a clamp and mean shift.(.46 and 7.5).
More testing in progress, but so far looks very promising!
Note - cut your learning rates in half vs ReLU, it learns very rapidly.
(GeneralRelu is an upcoming Relu with leakiness, mean shift and clamp):