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Autoencoder

Known as: Autoassociator, Diabolo network, Auto-encoder 
An autoencoder, autoassociator or Diabolo network is an artificial neural network used for unsupervised learning of efficient codings.The aim of an… Expand
Wikipedia

Papers overview

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Review
2020
Review
2020
An autoencoder is a specific type of a neural network, which is mainly designed to encode the input into a compressed and… Expand
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Review
2019
Review
2019
Deep learning (DL) is playing an increasingly important role in our lives. It has already made a huge impact in areas, such as… Expand
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Review
2019
Review
2019
Abstractive summarization has been studied using neural sequence transduction methods with datasets of large, paired document… Expand
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Review
2019
Review
2019
Abstract Nowadays, Deep Learning is the most attractive research trend in the area of Machine Learning. With the ability of… Expand
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Review
2019
Review
2019
Many online applications, such as online social networks or knowledge bases, are often attacked by malicious users who commit… Expand
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Highly Cited
2016
Highly Cited
2016
The variational autoencoder (VAE; Kingma, Welling (2014)) is a recently proposed generative model pairing a top-down generative… Expand
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Highly Cited
2015
Highly Cited
2015
In this paper, we propose the “adversarial autoencoder” (AAE), which is a probabilistic autoencoder that uses the recently… Expand
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Highly Cited
2012
Highly Cited
2012
  • P. Baldi
  • ICML Unsupervised and Transfer Learning
  • 2012
  • Corpus ID: 10921035
Autoencoders play a fundamental role in unsupervised learning and in deep architectures for transfer learning and other tasks. In… Expand
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Highly Cited
2010
Highly Cited
2010
We explore an original strategy for building deep networks, based on stacking layers of denoising autoencoders which are trained… Expand
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Highly Cited
2008
Highly Cited
2008
Previous work has shown that the difficulties in learning deep generative or discriminative models can be overcome by an initial… Expand
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