3 papers
cs.LG2025
Leveraging graph neural networks and mobility data for COVID-19 forecasting
Fernando H. O. Duarte, Gladston J. P. Moreira, Eduardo J. S. Luz +2
The COVID-19 pandemic has claimed millions of lives, spurring the development of diverse forecasting models. In this context, the true utility of complex spatio-temporal architectu…
physics.soc-ph2022
Flood risk map from hydrological and mobility data: a case study in São Paulo (Brazil)
Lívia Rodrigues Tomás, Giovanni Guarnieri Soares, Aurelienne A. S. Jorge +3
Cities increasingly face flood risk primarily due to extensive changes of the natural land cover to built-up areas with impervious surfaces. In urban areas, flood impacts come main…
math.NA2021
Adaptive modelling of variably saturated seepage problems
Ben Ashby, Cassiano Bortolozo, Alex Lukyanov +1
In this article we present a goal-oriented adaptive finite element method for a class of subsurface flow problems in porous media, which exhibit seepage faces. We focus on a repres…