A Manifold Learning Perspective on Representation Learning: Learning Decoder and Representations without an Encoder
Autoencoders are commonly used in representation learning. They consist of an encoder and a decoder, which provide a straightforward method to map <i>n</i>-dimensional data in input space to a lower <i>m</i>-dimensional representation space and back. The decoder itself define...
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| Auteurs principaux: | , |
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| Format: | article |
| Langue: | EN |
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MDPI AG
2021
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| Accès en ligne: | https://doaj.org/article/d20c216f39bc4836996f2afcc9ba9edc |
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