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Norse: A library for gradient-based learning in Spiking Neural Networks

Oak Ridge National Laboratory

Hosted by SNUFA

· 70 minutes
Oak Ridge, TN, USA · Hybrid

Recording

Abstract

Norse aims to exploit the advantages of bio-inspired neural components, which are sparse and event-driven - a fundamental difference from artificial neural networks. Norse expands PyTorch with primitives for bio-inspired neural components, bringing you two advantages: a modern and proven infrastructure based on PyTorch and deep learning-compatible spiking neural network components.

Topics

PyTorchSpiking Neural Networksbio-inspiredbio-inspired neural componentsdeep learningevent-drivengradient-based learningneural network infrastructure
More topics
norseprimitivessparse

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