【KDD 2021】STGODE : Spatial-Temporal Graph ODE Networks for Traffic Flow ForecastingLMissher 电子科技大学 计算机科学技术博士在读34 人赞同了该文章Preliminary 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。
相比之下,STG-NODE 生成基于 ODE 的动态图,并正确对齐动作的关键点。 STG-NODE 模型的基本框架主要由三部分组成:常微分方程-时间卷积网络(ODE-TCN)模块、图卷积网络-时间卷积网络(GCN-TCN)模块和输出模块。 ODE-TCN模块由串联的积分器、求解器和时间卷积网络组成。积分器通过积分函数来实现,以生成解函数,该解函...
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...
To this end, we propose Spatial-Temporal Graph Ordinary Differential Equation Networks (STGODE). Specifically, we capture spatial-temporal dynamics through a tensor-based ordinary differential equation (ODE), as a result, deeper networks can be constructed and spatial-temporal features are utilized ...
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 ...
29.Spatiotemporal graph queries on geographic databases under a conceptual abstraction scale 机译:概念抽象尺度下的地理数据库时空图查询 作者:Panagiotis Partsinevelos;Konstantinos Papadakis;Konstantinos Makantasis 期刊名称:《Geo-spatial information science》 | 2014年第2期 30.Two new hyperspectral indices ...
Spatial-temporal graph ode networks for traffic flow forecasting. In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, Singapore, 14–18 August 2021; pp. 364–373. [Google Scholar] Lu, Y.; Zhong, A.; Li, Q.; Dong, B. Beyond finite layer neural ...
CarloLucibello/GraphNeuralNetworks.jl: Graph Neural Networks in Julia FluxML/GeometricFlux.jl: Geometric Deep Learning for Flux Python: pyg-team/pytorch_geometric: Graph Neural Network Library for PyTorch benedekrozemberczki/pytorch_geometric_temporal: PyTorch Geometric Temporal: Spatiotemporal Signal Proce...
In this paper, we propose a new stochastic model that incorporates transportation between regions and at the same time enables spatial and temporal heterogeneity of transmission parameters. We model n regions as a graph having n nodes, and the transportation pattern between the regions is encoded as...
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 ...