Temporal knowledge graph embedding learningSpatial-temporal data miningTemporal knowledge graph completion, which aims to predict missing links in temporal knowledge graph (TKG), is an important research task due to the incompleteness of TKG. Recently, TKG embedding......
【一点点闲话】解读之前,先致敬原论文:Real Time Visual Tracking using Spatial-Aware Temporal Aggregation Network,这是今年8月份刚放在arxiv上的一篇文章,来自地平线的作品,主要是针对CVPR2018的一篇光流相关滤波文章【End-to-end Flow Correlation Tracking with Spatial-temporal Attention,原作者解读:CVPR2018视觉跟...
27.ROTAN: A Rotation-based Temporal Attention Network for Time-Specific Next POI Recommendatio 28. Diffusion-Based Cloud-Edge-Device Collaborative Learning for Next POI Recommendations 相关链接 2024 KDD( ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 知识发现和数据挖掘会议)在2024年8月...
关键词:持续学习,时空预测,流式数据 7. ST-ABC: Spatio-Temporal Attention-Based Convolutional Network for Multi-Scale Lane-Level Traffic Prediction 作者:Shuhao Li (Fudan University); Yue Cui (The Hong Kong University of Science and Technology); Libin Li (Guangzhou University); Weidong Yang (Fudan...
Location-based Graph Neural Network 更新边的特征 更新点的特征 更新全局图的特征 Spatial-temporal Attention Net 对于时间切片 对于空间切片 使用注意力机制,X是3维特征矩阵,对于每一个交易记录 使用时间注意力机制,更新时间切片,在此基础上在使用空间注意力机制 ...
graph attention network (GAT)self-adaptive adjacency matrixspatial-temporal correlationtraffic speed prediction2024 Inst. of Scientific and Technical Information of China. All rights reserved.Considering the nonlinear structure and spatial-temporal correlation of traffic network, and the influence of...
a spatial-temporal attention-based convolutional network (STACN) that can leverage the advantages of an attention mechanism, a convolutional neural network and long short-term memory to extract text and numerical information for stock price prediction. Benefiting from the utilisation of an attention ...
2.1 The Spatial-Temporal Relation Module: 作者首先对基础的静态物体关系模型,由 MSRA组提出的Relation network for object detection,用于编码 context information 来进行物体检测的。 Object relation module (ORM): 基础物体关系模型的目标是:通过在一张静态图像上的其他物体进行信息的聚合,来增强输入的表观特征。
Temporal Latent Auto-Encoder: A Method for Probabilistic Multivariate Time Series Forecasting(AAAI 2021)设计了一种端到端的学习方法。原始的矩阵分解可以表示为Y=FX,进而可以表示为Y=FF'Y,该方法将原来的矩阵分解部分改为AutoEncoder,即通过Encoder隐式得到base序列,再通过Decoder还原原始序列。对于第二项时序约束...
Attention Based Spatial-Temporal Graph Convolutional Networks ASTGCN模型的总体框架。它由三个具有相同结构的独立组件组成,分别用于对历史数据的最近、日周期和周周期依赖性进行建模。 假设采样频率为每天采样q次,当前时间为t_0,预测窗口大小为T_p,我们截取时间轴上长度为T_h、T_d和T_w的三个时间序列段,分别作为...