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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 n-dimensional data in input space to a lower m-dimensional representation space and back. The decoder itself defines an m-dimensional manifold in input s...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8625121/ https://www.ncbi.nlm.nih.gov/pubmed/34828101 http://dx.doi.org/10.3390/e23111403 |