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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...
Tallennettuna:
| Julkaisussa: | Sci Rep |
|---|---|
| Päätekijät: | , , , , , |
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
Nature Publishing Group UK
2020
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7040000/ https://ncbi.nlm.nih.gov/pubmed/32094366 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-020-59801-x |
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