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Merge pull request #272 from bjarthur/bja/trainspikingnet
add TrainSpikingNet
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title: TrainSpikingNet | ||
tagline: "train a spiking recurrent neural network" | ||
maintainer: ben arthur | ||
#project type - Required. Pick one of the three options - delete the other two. | ||
project type: [Other] | ||
github link: https://github.com/SpikingNetwork/TrainSpikingNet.jl | ||
documentation link: https://github.com/SpikingNetwork/TrainSpikingNet.jl?tab=readme-ov-file | ||
installation instructions link: https://github.com/SpikingNetwork/TrainSpikingNet.jl?tab=readme-ov-file#installation | ||
preferred contact method: mailto:[email protected] | ||
how to cite text: "Arthur, Kim, Chen, Preibisch, and Darshan (2023), A scalable implementation of the recursive least-squares algorithm for training spiking neural networks" | ||
how to cite link: "https://doi.org/10.3389/fninf.2023.1099510" | ||
image file: ./trainspikingnet.png | ||
image caption: a recurrent neural network | ||
youtube url: https://www.youtube.com/watch?v=VWISCzC2kOs | ||
youtube caption: TrainSpikingNet talk at JuliaCon 2022 | ||
#Optional "tag" fields. Select tags from the provided options - delete the options that are not applicable. If you feel another option is required to describe your project, add it and then note this in your pull request. | ||
development team: [Scientific Computing Software] | ||
programming language: [Julia] | ||
open source license: [BSD-3 Clause] | ||
software type: [Command line application] | ||
use case: [Calcium imaging, Electrophysiology, Modelling, Neural recording] | ||
usage environment: [HPC cluster, Local installation] | ||
software ecosystem: [CUDA] | ||
supported file types: [] | ||
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TrainSpikingNet uses recursive least squares to train fluctation-driven spiking | ||
recurrent neural networks to recapitulate arbitrary temporal activity patterns. |