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Attention|based Spatial|Temporal Graph Convolutional ...


Attention-based Spatial-Temporal Graph Convolutional Recurrent ...

Title:Attention-based Spatial-Temporal Graph Convolutional Recurrent Networks for Traffic Forecasting ... Abstract:Traffic forecasting is one of ...

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- ...

Attention Based Spatial-Temporal Graph Convolutional Networks for ...

In this paper, we propose a novel attention based spatial-temporal graph con- volutional network (ASTGCN) model to solve traffic flow forecasting problem.

guoshnBJTU/ASTGCN-2019-pytorch - GitHub

Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting, AAAI 2019, pytorch version - guoshnBJTU/ASTGCN-2019-pytorch.

Attention based spatial-temporal graph convolutional networks for ...

In this p propose a novel attention based spatial-temporal gr volutional network (ASTGCN) model to solve tra forecasting problem. ASTGCN mainly consists of ...

Attention Based Spatial-Temporal Graph Convolutional Networks for ...

In this paper, we propose a novel attention based spatial-temporal graph convolutional network (ASTGCN) model to solve traffic flow forecasting problem.

Spatial Temporal Attention Graph Convolutional Networks with ...

Human action recognition has been actively proposed and widely applied to surveillance systems and sports analysis. The skeleton based method is robust to.

Attention based spatiotemporal graph attention networks for traffic ...

Each component stacks multiple spatiotemporal blocks constructed using the attention mechanism, dilated gated convolution, and graph attention network. The ...

Attention-Based Spatial-Temporal Graph Convolutional Recurrent ...

In this paper, we propose a novel spatial-temporal neural network framework: Attention-based Spatial-Temporal Graph Convolutional Recurrent Network (ASTGCRN).

A3T-GCN: Attention Temporal Graph Convolutional Network ... - arXiv

... spatial dependence based on the topology of the road network through the graph convolutional network. Moreover, the attention mechanism was ...

Multi-Attention Based Spatial-Temporal Graph Convolution ...

Traffic forecasting is a great challenge to effectively extract complex spatio-temporal patterns due to the dynamic and nonlinear spatio-temporal ...

An attention-based adaptive spatial–temporal graph convolutional ...

We propose an attention-based adaptive spatial–temporal graph convolutional network (AAST-GCN), aiming to achieve effective and efficient action representation ...

Attention Based Spatial-Temporal Graph Convolutional Networks for ...

In this paper, we propose a novel attention based spatial-temporal graph con- volutional network (ASTGCN) model to solve traffic flow forecasting problem.

Attention-Based Spatio-Temporal Graph Convolutional Networks

Spatio-temporal attention-based Graph Convolutional Networks will be the subject of the current review. The aim is to identify the status ...

Cross- and Context-Aware Attention Based Spatial-Temporal Graph ...

Graph convolutional networks (GCN) capture the spatial evolution of the number of visits to each location. Attention mechanism, including ...

lehaifeng/T-GCN: Temporal Graph Convolutional Network ... - GitHub

A3T-GCN: Attention Temporal Graph Convolutional Network for Traffic Forecasting ... based on spatial-temporal graph convolutional networks. We first construct a ...

Multi-View Spatial-Temporal Graph Convolutional Networks With ...

Then, an attention based spatial-temporal graph convolution is designed for the most relevant spatial-temporal features for sleep stage classification.

An Attention based Spatial Temporal Graph Convolutional Networks ...

An Attention-based Spatial Temporal-Graph Convolutional Network (AST-GCN) is proposed for predicting traffic flows.

Attention-based Spatial-Temporal Graph Convolutional Recurrent ...

Download Citation | Attention-based Spatial-Temporal Graph Convolutional Recurrent Networks for Traffic Forecasting | Traffic forecasting is one of the most ...

Multi-Attention Based Spatial-Temporal Graph Convolution ...

A spatial-temporal graph convolution network based on multi-attention mechanism is proposed to predict long-term traffic conditions of different locations ...