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Activation function

In computational networks, the activation function of a node defines the output of that node given an input or set of inputs. A standard computer… 
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Related topics

31 relations
Action potentialArtificial neural networkArtificial neuronAutoencoder

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2016
Highly Cited
2016
Noisy Activation Functions
Common nonlinear activation functions used in neural networks can cause training difficulties due to the saturation behavior of… 
Highly Cited
2005
Highly Cited
2005
Mechanistic models for the activation volume and rate sensitivity in metals with nanocrystalline grains and nano-scale twins
Highly Cited
2001
Highly Cited
2001
Fast Electron Transfer Kinetics on Multiwalled Carbon Nanotube Microbundle Electrodes
The rate of electron transfer at carbon electrodes depends on various factors such as the structure and morphology of the carbon… 
Highly Cited
2001
Highly Cited
2001
IKKα Provides an Essential Link between RANK Signaling and Cyclin D1 Expression during Mammary Gland Development
Highly Cited
1995
Highly Cited
1995
Simple kinetic models of petroleum formation. Part I : oil and gas generation from kerogen
Highly Cited
1995
Highly Cited
1995
Monolayers in Three Dimensions: NMR, SAXS, Thermal, and Electron Hopping Studies of Alkanethiol Stabilized Gold Clusters
Gold clusters stabilized by chemisorbed monolayers of octane-, dodecaneor hexadecanethiolate have been investigated in solution… 
Highly Cited
1993
Highly Cited
1993
Substitution of three amino acids switches receptor specificity of Gqα to that of Giα
AGONIST-BOUND receptors activate heterotrimeric (αβγ) G proteins by catalysing replacement of GDP bound to the α-subunit by GTP1… 
Highly Cited
1993
Highly Cited
1993
A Better Activation Function for Artificial Neural Networks
An activation function, possibly new, is proposed for use in digital simulation of artiicial neural networks, on the ground that… 
Highly Cited
1993
Highly Cited
1993
How to Choose an Activation Function
We study the complexity problem in artificial feedforward neural networks designed to approximate real valued functions of… 
Highly Cited
1989
Highly Cited
1989
Universal approximation using feedforward networks with non-sigmoid hidden layer activation functions
K.M. Hornik, M. Stinchcombe, and H. White (Univ. of California at San Diego, Dept. of Economics Discussion Paper, June 1988; to… 
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