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Harnessing heterogeneity in space with statistically guided meta-learning
Spatial data are ubiquitous, massively collected, and widely used to support critical decision-making in many societal domains, including public health (e.g., COVID-19 pandemic control), agricultural crop monitoring, transportation, etc. While recent advances in machine learning and deep learning of...
| Autores principales: | , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer London
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9994417/ https://www.ncbi.nlm.nih.gov/pubmed/37035130 http://dx.doi.org/10.1007/s10115-023-01847-0 |