Training Spiking Neural Networks in Pure Julia | Ben Arthur, Christopher Kim | JuliaCon 2022
Автор: The Julia Programming Language
Загружено: 2022-07-28
Просмотров: 1088
Описание:
Training artificial neural networks to recapitulate the dynamics of biological neuronal recordings has become a prominent tool to understand computations in the brain. We present an implementation of a recursive-least squares algorithm to train units in a recurrent spiking network. Our code can reproduce the activity of 50,000 neurons of a mouse performing a decision-making task in less than an hour of training time. It can scale to a million neurons on a GPU with 80 GB of memory.
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