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An Overview of Variational Autoencoders for Source Separation, Finance, and Bio-Signal Applications
Autoencoders are a self-supervised learning system where, during training, the output is an approximation of the input. Typically, autoencoders have three parts: Encoder (which produces a compressed latent space representation of the input data), the Latent Space (which retains the knowledge in the...
| 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/PMC8774760/ https://www.ncbi.nlm.nih.gov/pubmed/35052081 http://dx.doi.org/10.3390/e24010055 |