Knowledge distillation for spiking neural networks: aligning features and saliency
Spiking neural networks (SNNs) are renowned for their energy efficiency and bio-fidelity, but their widespread adoption is hindered by challenges in training, primarily due to the non-differentiability of spiking activations and limited representational capacity. Existing approaches, such as artific...
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Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
IOP Publishing
2025-01-01
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Series: | Neuromorphic Computing and Engineering |
Subjects: | |
Online Access: | https://doi.org/10.1088/2634-4386/ade821 |
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