In the context of artificial neural networks, the rectifier or ReLU (rectified linear unit) activation function is an activation function defined as the...
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%5B%5BWikipedia%3ARedirects+for+discussion%5D%5D+debate+closed+as+delete #REDIRECT Rectifier (neural networks)...
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Deep sparse rectifier neural networks (PDF). AISTATS. Archived from the original (PDF) on 2016-12-13. Retrieved 2023-04-10. Rectifier and softplus activation...
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A residual neural network (also referred to as a residual network or ResNet) is a seminal deep learning model in which the weight layers learn residual...
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recurrent neural networks and convolutional neural networks, renewed interest in ANNs. The 2010s, saw the development of a deep neural network (a neural network...
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to: Rectifier, a device for converting alternating current to direct current Rectifier (neural networks), an activation function for artificial neural networks...
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Deep learning (redirect from Deep neural networks)
architectures such as deep neural networks, deep belief networks, recurrent neural networks, convolutional neural networks and transformers have been...
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Activation function (category Artificial neural networks)
function. Logistic function Rectifier (neural networks) Stability (learning theory) Softmax function Hinkelmann, Knut. "Neural Networks, p. 7" (PDF). University...
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(hidden layers). A network is typically called a deep neural network if it has at least 2 hidden layers. Artificial neural networks are used for various...
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or loops, in contrast to recurrent neural networks, which have a bi-directional flow. Modern feedforward networks are trained using the backpropagation...
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