Skip to search formSkip to main contentSkip to account menu

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… 
Wikipedia

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2020
Highly Cited
2020
Implicitly defined, continuous, differentiable signal representations parameterized by neural networks have emerged as a powerful… 
Highly Cited
2020
Highly Cited
2020
Consider the multivariate nonparametric regression model. It is shown that estimators based on sparsely connected deep neural… 
Highly Cited
2019
Highly Cited
2019
The concept of non-linearity in a Neural Network is introduced by an activation function which serves an integral role in the… 
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… 
Highly Cited
2017
Highly Cited
2017
Very deep convolutional networks have been central to the largest advances in image recognition performance in recent years… 
Highly Cited
2017
Highly Cited
2017
The choice of activation functions in deep networks has a significant effect on the training dynamics and task performance… 
Highly Cited
2011
Highly Cited
2011
While logistic sigmoid neurons are more biologically plausible than hyperbolic tangent neurons, the latter work better for… 
Highly Cited
2011
Highly Cited
2011
The activation function used to transform the activation level of a unit (neuron) into an output signal. There are a number of… 
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… 
Highly Cited
1990
Highly Cited
1990
  • D. Specht
  • Neural Networks
  • 1990
  • Corpus ID: 15189518