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UID:pretalx-juliacon2021-X9RATL@pretalx.com
DTSTART:20210729T133000Z
DTEND:20210729T134000Z
DESCRIPTION:The aim of this work is to evaluate the feasibility of re-imple
 menting some key parts of the widely used Weather Research and Forecasting
  WRF-SFIRE simulator by replacing its core differential equations numerica
 l solvers with state-of-the-art physics-informed machine learning techniqu
 es to solve ODEs and PDEs implemented in Julia\, in order to transform it 
 into a real-time simulator for wildfire spread prediction.
DTSTAMP:20260715T094945Z
LOCATION:Green
SUMMARY:Physics-Informed ML Simulator for Wildfire Propagation - Francesco 
 Calisto\, Simone Azeglio\, Valerio Pagliarino\, Luca Bottero
URL:https://pretalx.com/juliacon2021/talk/X9RATL/
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