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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-10-01
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| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/23/11/1403 |