A Comprehensive Review of Spiking Neural Networks: Interpretation, Optimization, Efficiency, and Best Practices

March 19, 2023 ยท The Cartographer ยท ๐Ÿ› arXiv.org

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
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"Title-pattern auto-detect: A Comprehensive Review of Spiking Neural Networks: Interpretation, Optimization, Efficiency, and Bes"

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Authors Kai Malcolm, Josue Casco-Rodriguez arXiv ID 2303.10780 Category cs.NE: Neural & Evolutionary Cross-listed cs.LG, eess.IV Citations 22 Venue arXiv.org Last Checked 2 days ago
Abstract
Biological neural networks continue to inspire breakthroughs in neural network performance. And yet, one key area of neural computation that has been under-appreciated and under-investigated is biologically plausible, energy-efficient spiking neural networks, whose potential is especially attractive for low-power, mobile, or otherwise hardware-constrained settings. We present a literature review of recent developments in the interpretation, optimization, efficiency, and accuracy of spiking neural networks. Key contributions include identification, discussion, and comparison of cutting-edge methods in spiking neural network optimization, energy-efficiency, and evaluation, starting from first principles so as to be accessible to new practitioners.
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