Forecasting West Nile Virus With Graph Neural Networks: Harnessing Spatial Dependence in Irregularly Sampled Geospatial Data.

Tonks A, Harris T, Li B, Brown W, Smith R

DOI: 10.1029/2023gh000784
Published: 2024 Jul
Container: GeoHealth
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1029/2023gh000784,
  title = {Forecasting West Nile Virus With Graph Neural Networks: Harnessing Spatial Dependence in Irregularly Sampled Geospatial Data.},
  author = {Tonks A and Harris T and Li B and Brown W and Smith R},
  year = {2024},
  journal = {GeoHealth},
  doi = {10.1029/2023gh000784},
  url = {https://doi.org/10.1029/2023gh000784}
}

RIS

TY  - JOUR
TI  - Forecasting West Nile Virus With Graph Neural Networks: Harnessing Spatial Dependence in Irregularly Sampled Geospatial Data.
AU  - Tonks A
AU  - Harris T
AU  - Li B
AU  - Brown W
AU  - Smith R
PY  - 2024
JO  - GeoHealth
DO  - 10.1029/2023gh000784
UR  - https://doi.org/10.1029/2023gh000784
ER  -

APA

A, T., T, H., B, L., W, B., & R, S. (2024). Forecasting West Nile Virus With Graph Neural Networks: Harnessing Spatial Dependence in Irregularly Sampled Geospatial Data.. GeoHealth. https://doi.org/10.1029/2023gh000784

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pubmed · retrieved 2026-09-24T20:26:23.943Z