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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… Expand
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31 relations
Action potentialArtificial neural networkArtificial neuronAutoencoder
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2018
Highly Cited
2018
Searching for Activation Functions
The choice of activation functions in deep networks has a significant effect on the training dynamics and task performance… Expand
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Highly Cited
2017
Highly Cited
2017
Swish: a Self-Gated Activation Function
The choice of activation functions in deep networks has a significant effect on the training dynamics and task performance… Expand
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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… Expand
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Highly Cited
2015
Highly Cited
2015
Empirical Evaluation of Rectified Activations in Convolutional Network
In this paper we investigate the performance of different types of rectified activation functions in convolutional neural network… Expand
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Highly Cited
2015
Highly Cited
2015
Learning Activation Functions to Improve Deep Neural Networks
Artificial neural networks typically have a fixed, non-linear activation function at each neuron. We have designed a novel form… Expand
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Highly Cited
2011
Highly Cited
2011
Performance Analysis of Various Activation Functions in Generalized MLP Architectures of Neural Networks
The activation function used to transform the activation level of a unit (neuron) into an output signal. There are a number of… Expand
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Highly Cited
2010
Highly Cited
2010
A new method for classification of ECG arrhythmias using neural network with adaptive activation function
In this study, new neural network models with adaptive activation function (NNAAF) were implemented to classify ECG arrhythmias… Expand
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Highly Cited
1993
Highly Cited
1993
Multilayer Feedforward Networks with a Non-Polynomial Activation Function Can Approximate Any Function
Several researchers characterized the activation function under which multilayer feedforwardnetworks can act as universal… Expand
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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… Expand
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1993
1993
How to Choose an Activation Function
We study the complexity problem in artificial feedforward neural networks designed to approximate real valued functions of… Expand
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