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about
P1346
P40
Deep learningVisualizing Data using t-SNELearning representations by back-propagating errorsImagenet classification with deep convolutional neural networksReplicated Softmax: an Undirected Topic ModelReducing the dimensionality of data with neural networksLearning distributed representations of conceptsGlove-Talk: a neural network interface between a data-glove and a speech synthesizer.A fast learning algorithm for deep belief nets.Training products of experts by minimizing contrastive divergence.Learning multiple layers of representation.Layer NormalizationTo recognize shapes, first learn to generate images.Learning to represent visual input.Lesioning an attractor network: investigations of acquired dyslexia.Discovering binary codes for documents by learning deep generative models.Why the islands move.Simulating brain damage.Generative models for discovering sparse distributed representations.Machine learning for neuroscience.Dynamic Routing Between CapsulesGlove-talk II - a neural-network interface which maps gestures to parallel formant speech synthesizer controls.Deep, narrow sigmoid belief networks are universal approximators.Glove-TalkII--a neural-network interface which maps gestures to parallel formant speech synthesizer controls.Where do features come from?Probabilistic sequential independent components analysis.An efficient learning procedure for deep Boltzmann machines.Attend, Infer, Repeat: Fast Scene Understanding with Generative ModelsUsing Fast Weights to Attend to the Recent PastVarieties of Helmholtz Machine.The Helmholtz machine.Separating figure from ground with a parallel network.How neural networks learn from experience.Modeling the manifolds of images of handwritten digits.Parallel visual computation.Variational learning for switching state-space models.Computation by neural networks.The "wake-sleep" algorithm for unsupervised neural networks.Comparing classification methods for longitudinal fMRI studies.Learning to represent spatial transformations with factored higher-order Boltzmann machines.
P50
description
Scienziato inglese di Intelligenza Artificiale
@it
britischer Wissenschaftler
@de
computer scientist and psychologist
@en
informaticien britannique
@fr
informaticus en psycholoog
@nl
informático teórico del Reino Unido
@es
دانشمند علوم کامپیوتر بریتانیایی
@fa
來自英國的計算機科學家和心理學家
@zh
來自英國的資訊科學家和心理學家
@zh-hant
來自英國的資訊科學家和心理學家
@zh-tw
name
Geoffrey E. Hinton
@da
Geoffrey E. Hinton
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Geoffrey E. Hinton
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Geoffrey E. Hinton
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Geoffrey E. Hinton
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Geoffrey E. Hinton
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Geoffrey Hinton
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Geoffrey Hinton
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Geoffrey Hinton
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Geoffrey Hinton
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Geoffrey E. Hinton
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Geoffrey E. Hinton
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Geoffrey E. Hinton
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Geoffrey E. Hinton
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Geoffrey E. Hinton
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Geoffrey Hinton
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Geoffrey Hinton
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Geoffrey Hinton
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Geoffrey Hinton
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Geoff Hinton
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Geoffrey E Hinton
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Geoffrey E Hinton
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Geoffrey E Hinton
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Geoffrey E. Hinton
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Geoffrey E. Hinton
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Geoffrey Everest Hinton
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Geoffrey Hinton
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Hinton GE
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Hinton GE
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Geoffrey E. Hinton
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Geoffrey E. Hinton
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Geoffrey E. Hinton
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Geoffrey E. Hinton
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Geoffrey E. Hinton
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Geoffrey E. Hinton
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Geoffrey Hinton
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Geoffrey Hinton
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Geoffrey Hinton
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Geoffrey Hinton
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