2.2. Spiking Residual Structure 现在也有基于反向传播的Spiking ResNet,但结构与ResNet类似。 3. Methods 3.1. Spiking Neuron Model 介绍现有的脉冲神经元模型,及数学公式。我上篇博文也写过,不加赘述了。 论文中使用代理梯度方法,也就是,将σ的梯度用于反向传播,σ是与不可微的阶跃函数形状类似的可微函数。 3.2...
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...
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 ...
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...
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...
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...
Deep learning in spiking neural networks Neural Networks Journal2019, Neural Networks Amirhossein Tavanaei, ... Anthony Maida 3 Deep learning in SNNs Deep learning uses an architecture with many layers of trainable parameters and has demonstrated outstanding performance in machine learning and AI appli...
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 ...
Transferring policy of deep reinforcement learning from simulation to reality for robotics Article14 December 2022 Introduction Spiking Neural Networks (SNNs) are often regarded as the third generation of Artificial Neural Networks (ANNs) because their functionality closely resembles that of the mammalian ...