A Two|stream Graph Convolutional Network based on Brain ...

Heterogeneous Graph Convolutional Neural Network via Hodge ...

Abstract. This study proposes a novel heterogeneous graph convolu- tional neural network (HGCNN) to handle complex brain fMRI data at.

Brain age predicted using graph convolutional neural network ...

To assess neonatal brain injuries, two pediatric ... The proposed graph-based convolutional network for brain age prediction.

Graph Convolutional Network with Morphometric Similarity ... - MICCAI

This paper presents a new graph convolutional framework for population-based schizophrenia classification that leverages graph-theoretical measures of ...

Papers with Code - GCN Explained

A Graph Convolutional Network, or GCN, is an approach for semi-supervised learning on graph-structured data. It is based on an efficient variant of ...

Stronger Multi-scale Deep Graph Convolutional Networks

be written as a product of a block Krylov matrix and a learnable parameter matrix in a special form. Based on this, we propose two GCN architectures that ...

Graph Convolutional Networks (GCN): From CNN point of view

Table of Content: 00:00 CNN Summary 00:58 Analogy of CNN with Graph 03:00 Self-loop connection 04:22 GCN paper link: ...

Skeleton-based Action Recognition with Two-Branch Graph ...

We proposed a new model that the three-dimensional skeleton data is put into both the Convolutional Neural Network (CNN) and the Graph Convolutional Neural ...

Drug repositioning with adaptive graph convolutional networks

For example, Fiscon and Paci (2021) developed a network-based method named SAveRUNNER for drug repurposing, which offers a promising framework to efficiently ...

Graph Convolutional Networks —Deep Learning on Graphs

Defining graph convolution · D, the degree matrix, is the diagonal matrix containing the number of edges attached to each vertex; · A, the adjacency matrix, ...

Multi-View Feature Enhancement Based on Self-Attention ... - OUCI

To address this issue, a new multi-view brain network feature enhancement method based on self-attention mechanism graph convolutional network (SA-GCN) is ...

A Two-Stream Graph Convolutional Neural Network for Dynamic ...

Using the graph convolutional network (GCN) is widespread in traffic flow forecasting. Existing GCN-based methods mostly rely on undirected spatial correlations ...

M-GCN: A Multimodal Graph Convolutional Network to Integrate ...

(2), we use two more graph convolutional ... Predicting healthy older adult's brain age based on structural connectivity networks using artificial neural networks ...

Tutorial on Graph Convolutional Networks in Brain Imaging

○ graph Fourier transform. ○ two types of graph convolutions. ○ spectral GCN: based on graph Laplacian. ○ spatial methods: approximation using neighbors ...

Deep Learning with Graph Convolutional Networks: An Overview ...

Under such a set of wavelet bases, the graph convolutional neural network satisfies locality, and the computational complexity of the graph ...

Temporal-Adaptive Graph Convolutional Network for Automated ...

pleted data-driven based graph topology information but also effectively capture dynamic variations of brain fMRI data. ... Two-stream adaptive graph ...

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

We propose a novel model of dynamic skeletons called Spatial-Temporal Graph Convolutional Networks (ST-GCN), which moves beyond the limitations of previous ...

Graph convolutional network for fMRI analysis based on connectivity ...

Here, we define graphs based on functional connectivity and present a connectivity-based graph convolutional network (cGCN) architecture for fMRI analysis. Such ...

Graph Neural Network Series 2 — Convolution on Graphs: Delving ...

Graph Convolutional Networks (GCNs) represent a specifically designed neural network architecture for processing graph data, capable of ...

Skeleton-Based Action Recognition With Shift Graph Convolutional ...

Two-stream. 3d convolutional neural network for skeleton-based action recognition. arXiv preprint arXiv:1705.08106, 2017. [15] Jun Liu, Amir Shahroudy ...

A double-branch graph convolutional network based on individual ...

List of references · Flesher, A brain-computer interface that evokes tactile sensations improves robotic arm control, Science, № 372, с. · Ganzer, Restoring the ...