BriefGPT.xyz
Apr, 2016
可微的加性和乘性神经元之间的转换
A Differentiable Transition Between Additive and Multiplicative Neurons
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Wiebke Köpp, Patrick van der Smagt, Sebastian Urban
TL;DR
介绍了一种基于非整数函数迭代数学概念的可参数化传递函数，能够使神经元执行的运算在加和乘法之间平滑、可微地调整，从而将加和乘法的决策集成到标准的反向传播训练程序中。
Abstract
Existing approaches to combine both
additive
and
multiplicative
neural units either use a fixed assignment of operations or require discrete optimization to determine what function a neuron should perform. Howeve
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