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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… 
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Related topics

Related topics

32 relations
Activation functionArtificial neural networkBackpropagationConjugate gradient method

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
Unsupervised Neural Categorization for Scientific Publications
Most conventional document categorization methods require a large number of documents with labeled categories for training. These… 
2018
2018
A Deep Learning Approach with an Attention Mechanism for Automatic Sleep Stage Classification
Automatic sleep staging is a challenging problem and state-of-the-art algorithms have not yet reached satisfactory performance to… 
2017
2017
A Novel Deep Neural Network that Uses Space-Time Features for Tracking and Recognizing a Moving Object
Abstract This work proposes a deep neural net (DNN) that accomplishes the reliable visual recognition of a chosen object captured… 
2017
2017
A Probabilistic Framework for Multi-Label Learning with Unseen Labels
We present a probabilistic framework for multi-label learning for the setting when the test data may require predicting labels… 
2016
2016
Deep SRN for robust object recognition: A case study with NAO humanoid robot
In recent years, deep neural networks have shown excellent performance for solving complex object recognition tasks. The increase… 
2012
2012
Appendix: Building high-level features using large scale unsupervised learning
In this appendix, we discuss more details regarding the algorithm, its implementation, test set for 3D-transformed faces… 
2012
2012
Layer-wise learning of deep generative models
When using deep, multi-layered architectures to build generative models of data, it is difficult to train all layers at once. We… 
2007
2007
Condition Monitoring of HV Bushings in the Presence of Missing Data Using Evolutionary Computing
The work proposes the application of neural networks with particle swarm optimisation (PSO) and genetic algorithms (GA) to… 
Highly Cited
2001
Highly Cited
2001
A nonlinear neural network model of mixture of local principal component analysis: application to handwritten digits recognition
Highly Cited
1990
Highly Cited
1990
Extracting features from faces using compression networks: Face
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