nLab spiking neural network




A spiking neural network is a neural network which behaves in a time dependent manner similar to biological neurons: neurons only send a signal only when a threshold is reached.

See also


  • Amirhossein Tavanaei, Masoud Ghodrati, Saeed Reza Kheradpisheh, Timothee Masquelier, Anthony S. Maida, Deep Learning in Spiking Neural Networks, Neural Networks, Volume 111, March 2019, Pages 47-63 (arXiv:1804.08150, doi:10.1016/j.neunet.2018.12.002)

  • Milad Mozafari, Mohammad Ganjtabesh, Abbas Nowzari-Dalini, Timothée Masquelier, SpykeTorch: Efficient Simulation of Convolutional Spiking Neural Networks with at most one Spike per Neuron, Frontiers in Neuroscience, 13:625. (arXiv:1903.02440, doi:10.3389/fnins.2019.00625)

  • Benjamin Cramer, Sebastian Billaudelle, Simeon Kanya, Aron Leibfried, Andreas Grübl, Vitali Karasenko, Christian Pehle, Korbinian Schreiber, Yannik Stradmann, Johannes Weis, Johannes Schemmel, Friedemann Zenke, Surrogate gradients for analog neuromorphic computing, Proceedings of the National Academy of Sciences of the United States of America?, Volume 119, No. 4, January 14, 2022 (arXiv:2006.07239, doi:10.1073/pnas.2109194119)

  • Shikhar Gupta, Arpan Vyas, Gaurav Trivedi, FPGA Implementation of Simplified Spiking Neural Network (arXiv:2010.01200)

  • Youngeun Kim, Priyadarshini Panda, Revisiting Batch Normalization for Training Low-latency Deep Spiking Neural Networks from Scratch (arXiv:2010.01729)

  • Youngeun Kim, Priyadarshini Panda, Visual Explanations from Spiking Neural Networks using Interspike Intervals, (arXiv:2103.14441)

  • Zhehui Wang, Xiaozhe Gu, Rick Goh, Joey Tianyi Zhou, Tao Luo, Efficient Spiking Neural Networks with Radix Encoding (arXiv:2105.06943)

  • Jason K. Eshraghian, Max Ward, Emre Neftci, Xinxin Wang, Gregor Lenz, Girish Dwivedi, Mohammed Bennamoun, Doo Seok Jeong, Wei D. Lu, Training Spiking Neural Networks Using Lessons From Deep Learning, (arXiv:2109.12894)

Wikipedia article: Spiking neural network

Created on October 18, 2022 at 06:32:38. See the history of this page for a list of all contributions to it.