Multi|view dual|channel graph convolutional networks with multi ...

Multi-view dual-channel graph convolutional networks with multi ...

A novel approach is proposed to address the problem of insufficient information consideration in network embedding, which is termed multi-task-oriented ...

(PDF) Multi-view dual-channel graph convolutional networks with ...

We firstly use kNN graph construction method to generate three views for each network dataset. Then, the proposed TAD-GCN contains dual-channel GCN which can ...

Multi-View Graph Convolutional Network for Multimedia ... - arXiv

Information systems → Recommender systems; Multimedia and multimodal retrieval. KEYWORDS. Multimedia recommendation, Graph Neural Network, Multi-View,. Self- ...

MVMA-GCN: Multi-view multi-layer attention graph convolutional ...

Graph structure is naturally suited for representing network structure, and Graph Neural Networks (GNNs) provide a practical framework for graph representation ...

Dual-channel deep graph convolutional neural networks - Frontiers

The dual-channel graph convolutional neural networks based on hybrid features jointly model the different features of networks, so that the features can learn ...

Multi-Channel Graph Neural Networks - IJCAI

Given the graphs learned with the series of convolutional fil- ters, the pooling algorithm clusters nodes in different ways to encode the multi-view pooled ...

Multi-Channel Graph Convolutional Networks for Graphs with ...

Graph convolutional networks (GCNs) have attracted increasing attention in various fields due to their significant capacity to process graph-structured data ...

AM-GCN: Adaptive Multi-channel Graph Convolutional Networks

AM-GCN: Adaptive Multi-channel Graph Convolutional Networks - zhumeiqiBUPT/AM-GCN.

Multi-view Graph Convolutional Networks with Differentiable Node ...

Abstract:Multi-view data containing complementary and consensus information can facilitate representation learning by exploiting the intact ...

AMSC: Adaptive Multi-channel Graph Convolutional Network ...

This paper proposes an adaptive multi-channel GCN-enhanced Web services classification method. In this method, we first extract specific and shared embedding.

Multi-View Graph Convolutional Network for Multimedia ...

We propose a novel Multi-View Graph Convolutional Network (MGCN) for the multimedia recommendation. Specifically, to avoid modality noise contamination.

Multi-view dual-channel graph convolutional networks with ... - OUCI

AbstractNetwork embedding has been extensively used in several practical applications and achieved great success. However, existing studies mainly focus on ...

Multi-view graph convolutional networks with attention mechanism

Recent advances in graph convolutional networks (GCNs), which mainly focus on how to exploit information from different hops of neighbors in an efficient ...

Multi-View Attribute Graph Convolution Networks for Clustering - IJCAI

In this paper, we propose a novel Multi-View Attribute Graph Convolution Networks (MAGCN) model for the clustering task. MAGCN is designed with two-pathway ...

Enhanced Multi-Channel Graph Convolutional Network for Aspect ...

In this paper, we propose an Enhanced Multi-Channel Graph Convolutional Network model (EMC-GCN) to fully utilize the relations between words.

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

Specifically, 1) we construct two brain view graphs based on the spatial proximity and functional connectivity of the brain, where each EEG channel corresponds ...

Multi-view graph convolutional networks with attention mechanism

This work proposes a novel model called Dual-channel Progressive Graph Convolutional Network (DPGCN) via sub-graph sampling, which possesses superior ...

Multi-View Graph Convolutional Networks with Differentiable Node ...

MGCN-DNS accepts multi-channel graph-structural data as inputs and aims to learn more robust graph fusion through a differentiable neural network. The ...

Multi-View Graph Convolutional Networks with Differentiable Node ...

MGCN-DNS accepts multi-channel graph-structural data as inputs and aims to learn more robust graph fusion through a differentiable neural ...

A Semi supervised Multi channel Graph Convolutional Network for ...

A Semi supervised Multi channel Graph Convolutional Network for Query Classification in E commerce. 15 views · 3 months ago ...more ...