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PRODID:-//pretalx//pretalx.com//juliacon-2022//speaker//BJR7KW
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UID:pretalx-juliacon-2022-UTTHUM@pretalx.com
DTSTART:20220728T173000Z
DTEND:20220728T174000Z
DESCRIPTION:Training artificial neural networks to recapitulate the dynamic
 s of biological neuronal recordings has become a prominent tool to underst
 and computations in the brain. We present an implementation of a recursive
 -least squares algorithm to train units in a recurrent spiking network.  O
 ur code can reproduce the activity of 50\,000 neurons of a mouse performin
 g a decision-making task in less than an hour of training time. It can sca
 le to a million neurons on a GPU with 80 GB of memory.
DTSTAMP:20260314T023232Z
LOCATION:Blue
SUMMARY:Training Spiking Neural Networks in pure Julia - Ben Arthur\, Chris
 topher Kim
URL:https://pretalx.com/juliacon-2022/talk/UTTHUM/
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