Bearing fault diagnosisSemi-supervised learningGraph attention networkLimited labeled samplesTriplet-channel graph construction method is designed for data complementarity.Spatial-temporal similar graph attention network learns spatiotemporal features.Graph contrastive learning is proposed to deeply mine features ...
论文笔记《Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting》,程序员大本营,技术文章内容聚合第一站。
However, little attention has been given to solving the difficult problem of extracting long-range dependencies without succumbing to the oversmoothing problem that is inherent in GCN-related architectures. This paper presents a groundbreaking ODE-based spatiotemporal forecasting model called STG-NODE. ...
To represent the evolving maritime situation, we establish an Adaptive Graph Spatial-Temporal Attention Network (AGSTAN). In this respect, we develop a dynamic spatial graph module that enable Graph Attention Network (GAT) model to learn adaptive spatial interactions between different latitude-longitude...
warp公式如下(p代表一个2维位置(x,y)): aggregation后得到的结果: 上式中的w是一个自适应权值,由文中提出的spatial-temporalattention机制决定。spatialattention使用余弦相似度来计算:temporalattention和大多数论文中的都差不多: 【AAAI-2019】论文速读——交通领域 ...
Then, the graph convolu-tional networks (GCN) are constructed for spatial structure feature reasoning in a single frame, which is consecutively followed by long short-term memory (LSTM) networks for temporal motion feature learning within the sequence. Moreover, the attention mechanism is further ...
原文:(PDF) Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting 现有的交通流预测方法大多缺乏对交通数据的动态时空相关性进行建模的能力,因此无法得到令人满意的预测结果。因此这篇文章提出了一种新的基于注意力的时空图卷积网络(Attention Based Spatial-Temporal Graph Convolutiona...
12 Correlation Attention Masked Temporal Transformer for User Identity Linkage using Heterogeneous Mobility Data 13 POI-Enhancer: An LLM-based Semantic Enhancement Framework for POI Representation Learning Poster 14 Graph Structure Learning for Spatial-Temporal Imputation: Adapting to Node and Feature Scales...
Beijing Jiaotong University Institute of Network Science and Intelligent System Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting Shengnan Guo, Youfang Lin, Ning Feng, Chao Song, HuaiyuWan∗ Introduction Background Many countries are committed to ...
Therefore, this work proposes a novel CSLR method based on spatial-temporal graph attention network (ST-GAT). The method aims to focus on local details and prevent the complex background in sign language datasets from interfering with the SLR. More precisely, OpenPose is utilized to detect the...