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Graph convolutional networks with the self|attention mechanism for ...


Graph convolutional networks with the self-attention mechanism for ...

A novel approach named graph convolutional networks with self-attention mechanism (ATGCN) is proposed to address the adaptive influence maximization as a ...

Self-Attention Empowered Graph Convolutional Network for ... - arXiv

This paper proposes a novel graph learning framework called the graph convolutional network with self-attention (GCN-SA).

On the Global Self-attention Mechanism for Graph Convolutional ...

Applying Global Self-attention (GSA) mechanism over features has achieved remarkable success on Convolutional Neural Networks (CNNs).

Self-attention empowered graph convolutional network for structure ...

This paper proposes a novel graph representation learning framework called the graph convolutional network with self-attention (GCN-SA).

A Self Attention-Based Graph Convolutional Approach ... - IEEE Xplore

Soft sensor methods based on deep neural networks have been widely developed nowadays. However, traditional deep learning models have insufficient ability ...

Attention mechanism-enhanced graph convolutional neural network ...

In this study, we propose a novel method for identifying lithology using an attention mechanism-enhanced graph convolutional neural network ...

Graph convolutional and attention models for entity classification in ...

Graph Attention Network (GAT) (Velickovic et al. 2018) is a graph neural network architecture that uses the attention mechanism to learn weights ...

Understanding Graph Attention Networks: A Practical Exploration

2- Self-Attention Mechanism: Each attention head computes its own attention coefficients: ... Convolutional Networks (GCNs) and Graph Attention ...

On the Global Self-attention Mechanism for Graph Convolutional ...

Applying Global Self-attention (GSA) mechanism over features has achieved remarkable success on Convolutional Neural Networks (CNNs). However, it is not clear ...

Multi-view graph convolutional networks with attention mechanism

Recently, graph neural networks [8], [9], particularly graph convolutional networks (GCNs) [10] have received careful attention in light of their favorable ...

Dynamic graph convolutional networks with attention mechanism for ...

In this study, we propose novel graph convolutional networks with attention mechanisms, named Dynamic GCN, for rumor detection.

Dynamic graph convolutional networks with attention mechanism for ...

In this study, we propose novel graph convolutional networks with attention mechanisms, named Dynamic GCN, for rumor detection.

Global Self-Attention as a Replacement for Graph Convolution

We propose an extension to the transformer neural network architecture for general-purpose graph learning by adding a dedicated pathway for ...

Graph Attention Networks - Petar Veličković

Extending neural networks to be able to properly deal with this kind of data is therefore a very important direction for machine learning research, but one that ...

AttPool: Towards Hierarchical Feature Representation in Graph ...

Graph convolutional networks (GCNs) are potentially insufficient in the ability to learn hierarchical representa- tion for graph embedding, which holds them ...

Spatial-MGCN: a novel multi-view graph convolutional network for ...

... graph convolutional network for identifying spatial domains with attention mechanism ... graph neural networks and self-supervised ...

A semi-supervised approach for the integration of multi-omics data ...

... self-attention mechanism and Graph Convolutional Networks(GCN), with the aim of enhancing the accuracy of complex disease classification ...

Multistep Flow Prediction on Car-Sharing Systems: A Multi-Graph ...

In this paper, we propose an attention multi-graph convolutional sequence- to-sequence model (AMGC-Seq2Seq), which is a novel deep learning model for multistep ...

STA-GCN: Spatial-Temporal Self-Attention Graph Convolutional ...

[15] proposed a graph convolutional network (GCN) based on a spatial–temporal attention mechanism without considering the heterogeneity of different time ...

On the Global Self-attention Mechanism for Graph Convolutional ...

Request PDF | On Jan 10, 2021, Chen Wang and others published On the Global Self-attention Mechanism for Graph Convolutional Networks | Find, read and cite ...