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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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Action potential
Artificial neural network
Artificial neuron
Autoencoder
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Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2020
Highly Cited
2020
Implicit Neural Representations with Periodic Activation Functions
V. Sitzmann
,
Julien N. P. Martel
,
Alexander W. Bergman
,
David B. Lindell
,
G. Wetzstein
NeurIPS
2020
Corpus ID: 219720931
Implicitly defined, continuous, differentiable signal representations parameterized by neural networks have emerged as a powerful…
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Highly Cited
2020
Highly Cited
2020
Nonparametric regression using deep neural networks with ReLU activation function
J. Schmidt-Hieber
The Annals of Statistics
2020
Corpus ID: 29465096
Consider the multivariate nonparametric regression model. It is shown that estimators based on sparsely connected deep neural…
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Highly Cited
2019
Highly Cited
2019
Mish: A Self Regularized Non-Monotonic Neural Activation Function
Diganta Misra
ArXiv
2019
Corpus ID: 201645264
The concept of non-linearity in a Neural Network is introduced by an activation function which serves an integral role in the…
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Highly Cited
2018
Highly Cited
2018
Searching for Activation Functions
Prajit Ramachandran
,
Barret Zoph
,
Quoc V. Le
arXiv
2018
Corpus ID: 10919244
The choice of activation functions in deep networks has a significant effect on the training dynamics and task performance…
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Highly Cited
2017
Highly Cited
2017
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Christian Szegedy
,
S. Ioffe
,
Vincent Vanhoucke
,
Alexander A. Alemi
AAAI
2017
Corpus ID: 1023605
Very deep convolutional networks have been central to the largest advances in image recognition performance in recent years…
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Highly Cited
2017
Highly Cited
2017
Swish: a Self-Gated Activation Function
Prajit Ramachandran
,
Barret Zoph
,
Quoc V. Le
2017
Corpus ID: 196158220
The choice of activation functions in deep networks has a significant effect on the training dynamics and task performance…
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Highly Cited
2011
Highly Cited
2011
Deep Sparse Rectifier Neural Networks
Xavier Glorot
,
Antoine Bordes
,
Yoshua Bengio
AISTATS
2011
Corpus ID: 2239473
While logistic sigmoid neurons are more biologically plausible than hyperbolic tangent neurons, the latter work better for…
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Highly Cited
2011
Highly Cited
2011
Performance Analysis of Various Activation Functions in Generalized MLP Architectures of Neural Networks
B. Karlik
,
A. Olğaç
2011
Corpus ID: 174791561
The activation function used to transform the activation level of a unit (neuron) into an output signal. There are a number of…
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Highly Cited
1998
Highly Cited
1998
The Atomic Components of Thought
John R. Anderson
,
C. Lebiere
1998
Corpus ID: 142733964
Contents: Preface. J.R. Anderson, C. Lebiere, Introduction. J.R. Anderson, C. Lebiere, Knowledge Representation. J.R. Anderson, C…
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Highly Cited
1990
Highly Cited
1990
Probabilistic neural networks
D. Specht
Neural Networks
1990
Corpus ID: 15189518
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