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Synaptic weight

In neuroscience and computer science, synaptic weight refers to the strength or amplitude of a connection between two nodes, corresponding in biology… Expand
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Highly Cited
2017
Highly Cited
2017
We study the topmost weight matrix of neural network language models. We show that this matrix constitutes a valid word embedding… Expand
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Review
2015
Review
2015
We review our work towards achieving competitive performance (classification accuracies) for on-chip machine learning (ML) of… Expand
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Highly Cited
2015
Highly Cited
2015
Using two phase-change memory devices per synapse, a three-layer perceptron network with 164 885 synapses is trained on a subset… Expand
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Highly Cited
2014
Highly Cited
2014
Machine-Learning tasks are becoming pervasive in a broad range of domains, and in a broad range of systems (from embedded systems… Expand
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Highly Cited
2005
Highly Cited
2005
  • J., Á.
  • 2005
  • Corpus ID: 171087204
Gastric intubation was adopted to examine the effect of continuous nutrient supply on digestive development of the pig during the… Expand
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Highly Cited
1998
Highly Cited
1998
Standard methods for computing prediction intervals in nonlinear regression can be effectively applied to neural networks when… Expand
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Highly Cited
1994
Highly Cited
1994
where gsyn is the synaptic conductance and to is the time of transmitter release. This function peaks at a value of l / e at t… Expand
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Highly Cited
1992
Highly Cited
1992
Abstract Variance components for birth, weaning, yearling and final weight in Australian Hereford, Angus and Zebu Cross cattle… Expand
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Highly Cited
1992
Highly Cited
1992
Abstract In order to investigate derived scales for the utility, or subjective value of money, subjects were instructed to… Expand
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Highly Cited
1991
Highly Cited
1991
The method of Structural Risk Minimization refers to tuning the capacity of the classifier to the available amount of training… Expand
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