Kernel mean matching enhances risk estimation under spatial distribution shifts
Abstract Accurate risk estimation under distribution shifts is critical for deploying machine learning models in real-world spatial applications, from ecological forecasting to medical image analysis. Conventional methods such as No Weighting (NW) and Importance Weighting (IW) fail in spatially stru...
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| Principais autores: | , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Portfolio
2026-02-01
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| coleção: | Scientific Reports |
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| Acesso em linha: | https://doi.org/10.1038/s41598-026-36740-7 |
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