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Deep learning for irregularly and regularly missing data reconstruction
Deep learning (DL) is a powerful tool for mining features from data, which can theoretically avoid assumptions (e.g., linear events) constraining conventional interpolation methods. Motivated by this and inspired by image-to-image translation, we applied DL to irregularly and regularly missing data...
Autores principales: | Chai, Xintao, Gu, Hanming, Li, Feng, Duan, Hongyou, Hu, Xiaobo, Lin, Kai |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7040000/ https://www.ncbi.nlm.nih.gov/pubmed/32094366 http://dx.doi.org/10.1038/s41598-020-59801-x |
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