Forecasting the covid-19 space-time dynamics in brazil with convolutional graph neural networks and transport modals

HIGHLIGHTS

• who: Modals and collaborators from the (UNIVERSITY) have published the paper: Forecasting the COVID-19 Space-time Dynamics in Brazil with Convolutional Graph Neural Networks and Transport Modals, in the Journal: (JOURNAL)
• what: This study proposes a GNN-based single-model architecture to forecast the daily spatio-temporal dynamics of the pandemic, in terms of cases and deaths by SARS-CoV-2, according to the influence that certain regions (in general towns) exert on others. Show that the approach is sound to detect and anticipate patterns of infection and death based on influence regions and . . .
  

   

  

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