MDN首先从空间(MNIST)和时间(TIDigits)数据集生成,然后扩展到各种其他不同的时空任务(包括Fashion-MNIST、NETtalk、Cifar-10、TIMIT和N-MNIST)。与其他SOTA SNN算法相比,达到了相当的精度,并且使用MDN的SNN也比不使用MDN的SNN实现了更好的泛化。 Keywords: Spiking Neural Network, Biologically-plausible Computing, M...
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks (AAAI 2023) Jintang Li, Zhouxin Yu, Zulun Zhu, Liang Chen, Qi Yu, Zibin Zheng, Sheng Tian, Ruofan Wu, Changhua Meng This repository is an official PyTorch implementation of SpikeNet. Abstract Recent years have seen ...
Keywords: spiking neural networks, supervised learning, event driven processing, DVS sensors, convolutional neural networks, fully connected neural networks, neuromorphic 1. INTRODUCTION 深度学习和深度人工神经网络(LeCun et al., 2015; Schmidhuber, 2015)目前在几乎所有机器学习基准测试中都拥有最先进的性能,...
A graph neural network framework for dynamic reconfiguration in distribution grids.Introduce gated message passing to model switches in the grid.Design local predictors to enable scalability of the framework.Implement a physics-informed rounding algorithm for topology decisions.Results show GraPhyR is able...
The purpose of this paper is to infer a dynamic graph as a global (collective) model of time-varying measurements at a set of network nodes. This model captures both pairwise as well as higher order interactions (i.e., more than two nodes) among the nodes. The motivation of this work...
deep-learninggraph-neural-networksgraph-neural-networktemporal-networkdynamic-network-embeddingdynamic-graph-embeddingtemporal-graph 615stars 15watching 83forks Releases No releases published Packages No packages published Contributors4 Languages Shell100.0%...
Spiking neural networks (SNNs) which use spiking neurons as a component, have shown substantial promise in simulating biological neuron mechanisms and saving computing power. However, preset or suboptimal hyperparameters are still used for spiking neurons adopted in SNNs, and the heterogeneity of ...
et al. Role of graph architecture in controlling dynamical networks with applications to neural systems. Nat. Phys. 14, 91–98 (2018). CAS PubMed Google Scholar Stiso, J. et al. White matter network architecture guides direct electrical stimulation through optimal state transitions. Cell Rep....
DynamicPathPlanningwithSpikingNeuralNetworksUlrichRoth,MarcWalker,ArneHilmann,andHeinrichKlarTU-Berlin,InstitutfürMikroelektronik,Jebensstr.1..
A. Spiking Neural Networks (SNNs) SNN,第三代NN[20],与传统的DNN相比表现出更好的生物学合理性。事实上,SNN中神经元之间基于事件的通信类似于人脑的功能。SNN相对于传统DNN的另一个关键优势是,在Intel Loihi [8]或IBM TrueNorth [7]等神经形态芯片上实现时,它们提高了能效。此外,DVS传感器[9]的最新发展进...