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FastSpiker: Enabling Fast Training for Spiking Neural Networks on
  Event-based Data through Learning Rate Enhancements for Autonomous Embedded
  Systems

FastSpiker: Enabling Fast Training for Spiking Neural Networks on Event-based Data through Learning Rate Enhancements for Autonomous Embedded Systems

7 July 2024
Iqra Bano
Rachmad Vidya Wicaksana Putra
Alberto Marchisio
Muhammad Shafique
ArXivPDFHTML

Papers citing "FastSpiker: Enabling Fast Training for Spiking Neural Networks on Event-based Data through Learning Rate Enhancements for Autonomous Embedded Systems"

4 / 4 papers shown
Title
Embodied Neuromorphic Artificial Intelligence for Robotics:
  Perspectives, Challenges, and Research Development Stack
Embodied Neuromorphic Artificial Intelligence for Robotics: Perspectives, Challenges, and Research Development Stack
Rachmad Vidya Wicaksana Putra
Alberto Marchisio
F. Zayer
Jorge Dias
Muhammad Shafique
25
10
0
04 Apr 2024
TopSpark: A Timestep Optimization Methodology for Energy-Efficient
  Spiking Neural Networks on Autonomous Mobile Agents
TopSpark: A Timestep Optimization Methodology for Energy-Efficient Spiking Neural Networks on Autonomous Mobile Agents
Rachmad Vidya Wicaksana Putra
Muhammad Shafique
37
12
0
03 Mar 2023
lpSpikeCon: Enabling Low-Precision Spiking Neural Network Processing for
  Efficient Unsupervised Continual Learning on Autonomous Agents
lpSpikeCon: Enabling Low-Precision Spiking Neural Network Processing for Efficient Unsupervised Continual Learning on Autonomous Agents
Rachmad Vidya Wicaksana Putra
Muhammad Shafique
26
16
0
24 May 2022
A disciplined approach to neural network hyper-parameters: Part 1 --
  learning rate, batch size, momentum, and weight decay
A disciplined approach to neural network hyper-parameters: Part 1 -- learning rate, batch size, momentum, and weight decay
L. Smith
191
1,019
0
26 Mar 2018
1