STGODE是被kDD2021录用的最新的关于交通预测的文章,其将CGNN(continous graph neural network)应用于多变量时序预测中交通预测的文章。 基于路网的交通预测任务中,将基于历史的一段交通状况预测未来的一段交通状况。具体的,假设交通路网表示为 G=(V,E,A)。(其中 V 表示路网中传感器的集合并含有 N 个节点;E ...
To this end, the spatial-temporal graph neural ODE network (STG-NODE) proposed herein integrates well-designed components to overcome these challenges. As shown in Figure 1, compared with the traditional methods, STG-NODE has excellent advantages in terms of accurately identifying key actions. First...
In the field of skeleton-based action recognition, accurately recognizing human actions is crucial for applications such as virtual reality and motion analysis. However, this task faces challenges such intraindividual action differences and long-term temporal dependencies. To address these challenges, we...
21. Pre-Training Identification of Graph Winning Tickets in Adaptive Spatial-Temporal Graph Neural Networks 链接:arxiv.org/abs/2406.0828 代码:anonymous.4open.science 作者:Wenying Duan (Jiangxi Provincial Key Laboratory of Intelligent Systems and Human-Machine Interaction, Nanchang University); Tianxiang ...
Based on the above problems, we propose a new deep learning model MSSTGCN, which utilizes multi-head attention and spatial-temporal graph convolutional networks for multi-scale traffic flow prediction. By dividing traffic flow data into hourly, daily, and weekly scales, the periodic features in ...
Biological cells rely on precise spatiotemporal coordination of biochemical reactions to control their functions. Such cell signaling networks have been a common focus for mathematical models, but they remain challenging to simulate, particularly in realistic cell geometries. Here we present Spatial Modelin...
Rio, “Using BlazePose on Spatial Temporal Graph Convolutional Networks for Action Recognition,” Computers, Materials & Continua, vol. 74, no. 1, pp. 19–36, 2023, 10.32604/cmc.2023.032499. Google Scholar An et al., 2023 P. An, et al. Leveraging self-paced semi-supervised learning with ...
Int J Geogr Inf Sci 28(3):455–478 13 A scoping review on the multiplicity of scale in spatial analysis 323 Van de Weghe N, de Roo B, Qiang Y, Versichele M, Neutens T, de Maeyer P (2014) The continuous spatio-temporal model (CSTM) as an exhaustive framework for ...
By accepting loss of information when not considering single species, while acknowledging the advantages of low spatio-temporal complexity and eased communication of the results to stakeholders (Kontogianni et al., 2010), we decided to choose a more detailed differentiation of ecosystems according to ...
A 'directed graph' depicts the connectivity between nodes. In the absence of con- nectivity, nodes are 'insular'. In 'star networks' all nodes are connected to a central nucleus but otherwise are not mutually connected. In 'complete networks' all pairs of nodes are connected. 'Network ...