Synthetic single cell RNA sequencing data from small pilot studies using deep generative models
Abstract Deep generative models, such as variational autoencoders (VAEs) or deep Boltzmann machines (DBMs), can generate an arbitrary number of synthetic observations after being trained on an initial set of samples. This has mainly been investigated for imaging data but could also be useful for sin...
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Autores principales: | , , , , , |
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Formato: | article |
Lenguaje: | EN |
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Nature Portfolio
2021
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Acceso en línea: | https://doaj.org/article/959146bec92e4abe9a6e3406415aeb4b |
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