Autoencoder and Its Various Variants
The concept of autoencoder was originally proposed by LeCun in 1987, early works on autoencoder were used for dimensionality reduction or feature learning. Recently, with the popularity of deep learning research, autoencoder has been brought to the forefront of generative modeling. Many variants of...
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| Published in: | Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics pp. 415 - 419 |
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| Main Authors: | , , , |
| Format: | Conference Proceeding |
| Language: | English |
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IEEE
01.10.2018
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| ISSN: | 2577-1655 |
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| Abstract | The concept of autoencoder was originally proposed by LeCun in 1987, early works on autoencoder were used for dimensionality reduction or feature learning. Recently, with the popularity of deep learning research, autoencoder has been brought to the forefront of generative modeling. Many variants of autoencoder have been proposed by different researchers and have been successfully applied in many fields, such as computer vision, speech recognition and natural language processing. In this paper, we present a comprehensive survey on autoencoder and its various variants. Furthermore, we also present the lineage of the surveyed autoencoders. This paper can provide researchers engaged in related works with very valuable help. |
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| AbstractList | The concept of autoencoder was originally proposed by LeCun in 1987, early works on autoencoder were used for dimensionality reduction or feature learning. Recently, with the popularity of deep learning research, autoencoder has been brought to the forefront of generative modeling. Many variants of autoencoder have been proposed by different researchers and have been successfully applied in many fields, such as computer vision, speech recognition and natural language processing. In this paper, we present a comprehensive survey on autoencoder and its various variants. Furthermore, we also present the lineage of the surveyed autoencoders. This paper can provide researchers engaged in related works with very valuable help. |
| Author | Chen, Junfen He, Qiang Zhang, Sufang Zhai, Junhai |
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| SubjectTerms | autoencoder decoder deep learning feature learning generative model |
| Title | Autoencoder and Its Various Variants |
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