- Improved spatial–temporal graph convolutional networks for upper ...🔍
- Attention Based Spatial|Temporal Graph Convolutional Networks for ...🔍
- The basics of spatio|temporal graph neural networks🔍
- Spatial Downscaling of Streamflow Data with Attention Based Spatio ...🔍
- Spatial|temporal graph neural networks for groundwater data🔍
- A deep learning model with spatio|temporal graph convolutional ...🔍
- Source detection on networks using spatial temporal graph ...🔍
- Spatio|Temporal Joint Graph Convolutional Networks for Traffic ...🔍
Spatial Temporal Graph Convolutional Networks
Improved spatial–temporal graph convolutional networks for upper ...
The upper limb rigid body model is established to increase the constraints of biological behavior and improve the accuracy of human posture data ...
Attention Based Spatial-Temporal Graph Convolutional Networks for ...
ASTGCN mainly consists of three independent components to respectively model three temporal properties of traffic flows, i.e., recent, daily-periodic and weekly ...
The basics of spatio-temporal graph neural networks - YouTube
Graph machine learning has become very popular in recent years in the machine learning and engineering communities.
Spatial Downscaling of Streamflow Data with Attention Based Spatio ...
For both cases, we propose the ScaleGNN, a graph neural network based on Attention-Based Spatio-Temporal Graph Convolutional Networks (ASTGCN).
Spatial-temporal graph neural networks for groundwater data - Nature
This paper introduces a novel application of spatial-temporal graph neural networks (ST-GNNs) to predict groundwater levels.
A deep learning model with spatio-temporal graph convolutional ...
A water quality prediction method based on graph convolutional network (GCN) and long short-term memory neural network (LSTM), namely spatio- ...
Source detection on networks using spatial temporal graph ...
Recently, [11] proposed using graph convolutional network. (GCN) to solve source detection with improved efficiency and accuracy. The method takes as input a ...
Spatio-Temporal Joint Graph Convolutional Networks for Traffic ...
Recent studies focus on formulating the traffic forecasting as a spatio-temporal graph modeling problem. They typically construct a static spatial graph at ...
spatio-temporal graph convolutional networks
To tackle CSLR, most works in the literature employ visual fea- tures that capture signing appearance information via 2D convolu- tional neural networks (CNNs) ...
Multi‐branch angle aware spatial temporal graph convolutional ...
The model adopts the legacy Spatial Temporal Graph Neural Network (ST-GCN) as its backbone and relocates it to create independent ST-GCN ...
Adaptive Spatial-Temporal Graph Convolutional Networks for Sleep ...
The main advantage of the GraphSleepNet is to adaptively learn the intrinsic connection among different electroencephalogram (EEG) channels, represented by an ...
Shale Gas Production Forecasting with Well Interference Based on ...
Shale Gas Production Forecasting with Well Interference Based on Spatial-Temporal Graph Convolutional Network. Journal Collections: Data ...
Predicting Team Performance with Spatial Temporal Graph ...
We propose a new neural network architecture,Spatial Temporal Graph Convolutional Networks (ST-GCN),that uses a weighted graph to represent the spatial ...
Graph learning-based spatial-temporal graph convolutional neural ...
Graph Convolutional Neural Network (GCN) has been effectively used for traffic forecasting due to its excellent performance in modelling spatial dependencies.
Spatial-Temporal Attention Mechanism and Graph Convolutional ...
Spatial attention focuses on the dependence between roads in the graph structure, and temporal attention captures the time dependence between ...
Railway Delay Prediction with Spatial-Temporal Graph ...
Using this graph-based formulation, we apply the Spatial-Temporal Graph Convolutional Network (STGCN) model to predict cascading delays ...
Friendly Introduction to Temporal Graph Neural Networks ... - YouTube
Papers ▭▭▭▭▭▭▭▭▭▭▭▭ Temporal Graph Networks: https://arxiv.org/pdf/2006.10637.pdf (used for the intro) Pytorch Geometric ...
Spatial‐temporal correlation graph convolutional networks for traffic ...
To integrate the spatial and temporal information together, a spatial-temporal correlation graph structure is proposed to aggregate the spatial ...
Attention module-based spatial–temporal graph convolutional ...
The spatial–temporal graph convolutional networks (ST-GCN) automatically learn both the temporal and spatial features from the skeleton data and ...