Deep learningSpiking 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 ...
本文发现训练浅层的SNN models用soft reset获得更好的结果,但是深层的SNN models用hard reset效果更好。这个观点与2020年CVPR文章《RMP-SNN: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Network》相矛盾,但是后者用的是ANN2SNN的方法,可能机制不一样,只能跑...
深度SNN为使用新型基于事件的传感器、利用时间代码和局部片上学习提供了很好的机会,到目前为止,我们只是在实际应用中实现了这些优势的皮毛。 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...
In 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 supervised manner using backpropagation. Vast amounts of labeled training examples ...
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...
Keywords:Spiking neural networks, Deep reinforcement learning, Energy-efficient continuous control 1 Introduction 具有连续高维观察和动作空间的移动机器人正越来越多地被部署来解决复杂的实际任务。鉴于其有限的主板能量资源,迫切需要设计节能解决方案来对这些自主机器人进行连续控制。基于策略梯度的深度强化学习(DRL)方法...
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 ...
showing the inefficiencies in training deep SNN networks. Finally, we apply the learning rules found in our experiments to theAnt-v4benchmark in MuJoCo37showing an increase in performance of 4.4×compared to the state-of-the-art spiking network proposed for the same task5....
A library for deep learning with Spiking Neural Networks (SNN)powered by GeNN, a GPU enhanced Neuronal Network simulation environment. Installation Follow the instructions in https://genn-team.github.io/genn/documentation/5/installation.html to install PyGeNN. Clone this project Install mlGeNN with...