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Activation function
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11	Perceptrons Informatics 1 CG: Lecture 5 Reading: Mirella Lapata Add to Reading List Source URL: www.inf.ed.ac.uk Language: English - Date: 2016-01-21 10:51:51 Artificial neural networks Neuroscience Cybernetics Applied mathematics Perceptron Multilayer perceptron Connectionism Artificial neuron Frank Rosenblatt Activation function Biological neural network Feedforward neural network
12	Multilayer Perceptrons and Backpropagation Informatics 1 CG: Lecture 6 Mirella Lapata School of Informatics University of Edinburgh Add to Reading List Source URL: www.inf.ed.ac.uk Language: English - Date: 2016-01-31 15:41:31 Artificial neural networks Multilayer perceptron Feedforward neural network Perceptron Backpropagation Artificial neuron Activation function Connectionism Extreme learning machine Convolutional neural network
13	Multilayer Perceptrons and Backpropagation Informatics 1 CG: Lecture 6 Mirella Lapata Reading: Kevin Gurney’s Introduction to Neural Networks, Add to Reading List Source URL: www.inf.ed.ac.uk Language: English - Date: 2016-01-31 15:41:31 Artificial neural networks Multilayer perceptron Feedforward neural network Backpropagation Delta rule Perceptron Artificial neuron Activation function
14	Theano Tutorial Theano is a software package which allows you to write symbolic code and compile it onto diﬀerent architectures (in particular, CPU and GPU). It was developed by machine learning researchers at the Univ Add to Reading List Source URL: colinraffel.com Language: English - Date: 2015-12-30 23:12:51 Artificial neural networks Sigmoid function Artificial neuron Parameter Function Gradient descent Backpropagation Multilayer perceptron Activation function Theano Default argument Artificial intelligence
15	IEEE TRANSACTIONS ON NEURAL NETWORKS, VOL. 8, NO. 6, NOVEMBERNonlinear Backpropagation: Doing Backpropagation Without Derivatives of the Activation Function Add to Reading List Source URL: people.binf.ku.dk Language: English - Date: 2005-11-10 10:33:06
16	4 JANUARYaction by competing for, or preventing the function of, some component required for the activation of a Gly-PI-specific phospholipase C. One candidate for such a component has been suggested by recent rep Add to Reading List Source URL: cmgm.stanford.edu Language: English - Date: 2012-12-20 13:28:11
17	30 Years of Adaptive Neural Networks: Perceptron, Madaline, and Backpropagation BERNARD WIDROW, FELLOW, IEEE, Add to Reading List Source URL: www-isl.stanford.edu Language: English - Date: 2008-03-07 20:14:11 Artificial neural networks Machine learning Applied mathematics Cybernetics ADALINE Artificial neuron Perceptron Madaline Backpropagation Feedforward neural network Activation function Bernard Widrow
18	Improving the Learning Speed of 2-Layer Neural Networks by Choosing Initial Values of the Adaptive Weights Derrick Nguyen and Bernard Widrow Information Systems Laboratory Stanford University Stanford, CA 94305 Add to Reading List Source URL: www-isl.stanford.edu Language: English - Date: 2008-03-07 21:10:07 Artificial neural networks Applied mathematics Cybernetics Statistics Backpropagation Artificial neuron Perceptron Sigmoid function Activation function Deep learning
19	Deep Sparse Rectifier Neural Networks Xavier Glorot DIRO, Universit´e de Montr´eal Montr´eal, QC, Canada Add to Reading List Source URL: jmlr.csail.mit.edu Language: English - Date: 2011-06-30 04:28:55 Artificial neural networks Machine learning Applied mathematics Artificial intelligence Rectifier Deep learning Feature learning Autoencoder Backpropagation Sigmoid function Activation function Artificial neuron
20	Univerzita Karlova v Praze Matematicko-fyzik´aln´ı fakulta ´ PRACE ´ DIPLOMOVA Add to Reading List Source URL: s3-eu-west-1.amazonaws.com Language: English - Date: 2015-03-31 02:55:44 Artificial neural networks Neuroscience Applied mathematics Cybernetics Backpropagation Artificial neuron Feedforward neural network Neuron Activation function Sigmoid function Biological neural network Convolutional neural network