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PRODID:-//pretalx//pretalx.com//juliacon-2022//speaker//WEFNJW
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UID:pretalx-juliacon-2022-BEY33E@pretalx.com
DTSTART:20220728T114000Z
DTEND:20220728T115000Z
DESCRIPTION:Modeling the temporal evolution of complex networks is still an
  open challenge across many fields. Using the SciML ecosystem in Julia\, w
 e train and simplify a Neural ODE on the low-dimensional embeddings of a t
 emporal sequence of networks. In this way\, we discover a dynamical system
  representation of the network that allows us to predict its temporal evol
 ution. In the talk we’ll show how the tight integration of SciML\, Netwo
 rk\, and Matrix Algebra packages in Julia opens new modeling directions.
DTSTAMP:20260310T185622Z
LOCATION:Green
SUMMARY:Using SciML to predict the time evolution of a complex network. - A
 ndre Macleod
URL:https://pretalx.com/juliacon-2022/talk/BEY33E/
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