The work explores the integration of behavioral analytics and artificial intelligence (AI) techniques, specifically Graph Convolutional Networks (GCNs) and deep learning, to predict student academic ...

Massive MIMO (multiple-input multiple-output) detection is an important topic in wireless communication and various machine learning based methods have been developed recently for this task.

Graph-based semi-supervised learning (GSSL) has long been a research focus. Traditional methods are generally shallow learners, based on the cluster assumption. Recently, graph convolutional networks ...

Discovering microbes underlying disease traits opens up opportunities for the diagnosis and effective treatment of diseases. However, traditional methods are often based on biological experiments, ...

2.2 Graph convolution neural networks. The conventional convolutional neural network (GNN) has demonstrated considerable efficacy in image processing and various other domains, effectively capturing ...

A classification method of gastric cancer subtype based on residual graph convolution network. Can Liu 1,2 Yuchen Duan 1 Qingqing Zhou 1 Yongkang Wang 1,2 Yong Gao 1,2 Hongxing Kan 1,2 Jili Hu 1,2 * .