Search Results for author:
Found 3 papers, 0 papers with code
Spyker: High-performance Library for Spiking Deep Neural Networks
Several SNNs are implemented in this work with different learning rules (spike-timing-dependent plasticity and reinforcement learning) using Spyker that achieve significantly better runtimes, to prove the practicality of the library in the simulation of large-scale networks.
Models Developed for Spiking Neural Networks
Spiking neural networks (SNNs) have been around for a long time, and they have been investigated to understand the dynamics of the brain.
A Faster Approach to Spiking Deep Convolutional Neural Networks
The proposed structure fractionalizes runtime and introduces an efficient approach to deep convolutional SNNs.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
