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SUMMARY:Using SciML to predict the time evolution of a complex network. - 
 Andre Macleod
DTSTART:20220728T114000Z
DTEND:20220728T115000Z
DTSTAMP:20260818T203709Z
UID:pretalx-juliacon-2022-BEY33E@pretalx.com
DESCRIPTION:Modeling the temporal evolution of complex networks is still a
 n open challenge across many fields. Using the SciML ecosystem in Julia\, 
 we train and simplify a Neural ODE on the low-dimensional embeddings of a 
 temporal sequence of networks. In this way\, we discover a dynamical syste
 m representation of the network that allows us to predict its temporal evo
 lution. In the talk we’ll show how the tight integration of SciML\, Netw
 ork\, and Matrix Algebra packages in Julia opens new modeling directions.
LOCATION:Green
URL:https://pretalx.com/juliacon-2022/talk/BEY33E/
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