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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
Wikipedia

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2019
Review
2019
The growing interest in both the automation of machine learning and deep learning has inevitably led to the development of a wide… Expand
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Review
2019
Review
2019
A neuroscience method to understanding the brain is to find and study the preferred stimuli that highly activate an individual… Expand
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Review
2019
Review
2019
Much of recent machine learning has focused on deep learning, in which neural network weights are trained through variants of… Expand
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Review
2018
Review
2018
Deep neural networks have been successfully used in diverse emerging domains to solve real world complex problems with may more… Expand
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Highly Cited
2018
Highly Cited
2018
The choice of activation functions in deep networks has a significant effect on the training dynamics and task performance… Expand
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Review
2017
Review
2017
A major threat to the comfort of human life has been imposed by increased industrialization and urbanization. The generation and… Expand
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Highly Cited
2017
Highly Cited
2017
Very deep convolutional networks have been central to the largest advances in image recognition performance in recent years. One… Expand
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Highly Cited
2011
Highly Cited
2011
While logistic sigmoid neurons are more biologically plausible than hyperbolic tangent neurons, the latter work better for… Expand
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Highly Cited
1998
Highly Cited
1998
Contents: Preface. J.R. Anderson, C. Lebiere, Introduction. J.R. Anderson, C. Lebiere, Knowledge Representation. J.R. Anderson, C… Expand
Highly Cited
1993
Highly Cited
1993
Several researchers characterized the activation functions under which multilayer feedforwardnetworks can act as universal… Expand