Spatio-temporal dataNeural networksGraph convolutionAccurate traffic forecasting is of vital importance for the management and decision in intelligent transportation systems. Indeed, it is a nontrivial endeavor to predict future traffic conditions due to the complexity of spatial relationships and temporal ...
more advanced neighborhood aggregation methods54, scalable inference55and domain-specific applications20have been introduced. In general, a graph neural network performsRrounds of message passing, after which all nodes’ latent features
12. Scalable Spatiotemporal Graph Neural Networks 13. Learning Decomposed Spatial Relations for Multi-Variate Time-Series Modeling 14. c-NTPP: Learning Cluster-Aware Neural Temporal Point Process 15. Trafformer: Unify Time and Space in Traffc Prediction 16. Spatio-Temporal Meta-Graph Learning for ...
A Graph Neural Network with Spatio-Temporal Attention for Multi-Sources Time Series Data: An Application to Frost Forecast frost forecastinggraph neural networksspatio-temporal attentionFrost forecast is an important issue in climate research because of its economic impact on several... N Sanchez-Pi ...
To further reduce latency, temporal pruning is performed by gradually reducing the timesteps while training. The networks are trained using surrogate gradient descent based backpropagation and we validate the results on CIFAR10 and CIFAR100, using VGG architectures. The spatiotemporally pruned SNNs ...
《Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting》,程序员大本营,技术文章内容聚合第一站。
the paper "Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting" 文章全部内容+对应ppt请查看:STGCN-keras 问题定义 如何准确的进行中长期的交通预测(中长期:over 30 minutes) 本篇论文主要是对地点的速度进行预测 ...
随着深度学习的快速发展,传统的卷积神经网络(Convolutional Neural Networks, CNNs)在计算机视觉领域取得了巨大的成功。然而,对于一些涉及到时序和空间信息的任务,如视频分析、动作识别和人体姿态估计等,传统的CNNs存在一定的局限性。为了有效地处理这些时空信息,研究人员提出了一种新型的卷积神经网络模型,即时空卷积网络(...
文中首先提出一般CTR预估模型会忽略其他广告与当前广告的关系,而这些广告却对当前广告是否被点击有很大的影响,然后从空间域、时间域上提出了三种辅助广告:上下文广告、历史点击过的广告、历史曝光未点击的广告。 历史点击过的广告、历史曝光未点击的广告不用解释了,属于时间域。下面说下空间域的上下文广告,如图1: 图1...
《Spatio-Temporal Backpropagation for Training High-performance Spiking Neural Networks》笔记 ABSTRACT STBP:Spatio-Temporal Backpropagation 1.探索SNN的一个重要原因:spikes的相关编码可以包含很多的时空信息。 2.目前很多(这篇文章发之前)研究都只关注于神经网络的空间域信息,造成了相关研究的瓶颈。也有部分只研究...