Spiking ResNet vs. SEW ResNet.我们首先通过用基本块替换SEW块,将SEW ResNet与ADD元素函数(SEW ADD ResNet)和Spiking ResNet的性能进行比较。如图9和表4所示,尽管Spiking ResNet(蓝色曲线)的训练损失低于SEW ADD ResNet(橙色曲线),但测试精度低于SEW ADD ResNet(90.97% v.s. 97.92%),这意味着Spiking ResNe...
现有的Spiking ResNet都是参照ANN中的标准残差块,简单地把ReLu激活函数层换成spiking neurons,所以说会发生degradation的问题(深网络比浅网络有更高的training los)并且很难实现残差学习。这篇文章提出了新框架spike-element-wise(SEW) ResNet,实现了deep SNNs的residual learning并且证明了SEW ResNet能够轻松实现identity...
Analog monolayer SWCNTs-based memristive 2D structure for energy-efficient deep learning in spiking neural networks Advances in materials science and memory devices work in tandem for the evolution of Artificial Intelligence systems. Energy-efficient computation is the u... H Abunahla,Y Abbas,A Geb...
Spiking neural networkBiological plausibilityMachine learningPower-efficient architectureIn recent years, deep learning has revolutionized the field of machine learning, for computer vision in particular. In this approach, a deep (multilayer) artificial neural network (ANN) is trained, most often in a ...
weili21:《Deep Residual Learning in Spiking Neural Networks》笔记5 赞同 · 4 评论文章 还有STBP-tdBN这篇文章: weili21:tdBN—《Going Deeper With Directly-Trained Larger Spiking Neural Networks》22 赞同 · 29 评论文章 Abstract 直接训练深度SNNs,采用代理梯度的BP算法 ...
Keywords: neural networks, spiking neurons, neuromorphic engineering, event-based computing, deep learning, binary networks 1. INTRODUCTION 使用深度神经网络(DNN)进行训练和推理,通常称为深度学习(LeCun et al., 2015; Schmidhuber, 2015; Goodfellow et al., 2016),为人工智能(AI)的许多引人注目的成功案例...
Keywords: neural networks, spiking neurons, neuromorphic engineering, event-based computing, deep learning, binary networks 1. INTRODUCTION 使用深度神经网络(DNN)进行训练和推理,通常称为深度学习(LeCun et al., 2015; Schmidhuber, 2015; Goodfellow et al., 2016),为人工智能(AI)的许多引人注目的成功案例...
Norse expands PyTorch with primitives for bio-inspired neural components, bringing you two advantages: a modern and proven infrastructure based on PyTorch and deep learning-compatible spiking neural network components. Documentation: norse.github.io/norse/ 1. Getting started The fastest way to try ...
A deep learning library for spiking neural networks which is based on PyTorch, focuses on fast training and supports inference on neuromorphic hardware. - synsense/sinabs
Communication by rare, binary spikes is a key factor for the energy efficiency of biological brains. However, it is harder to train biologically-inspired spiking neural networks than artificial neural networks. This is puzzling given that theoretical res