Alzheimer's Disease (AD), a leading neurodegenerative disorder, presents significant global health challenges. Advances in graph neural networks (GNNs) offer promising tools for analyzing multimodal ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein function prediction is essential for elucidating biological processes and ...

Google published details of a new kind of AI based on graphs called a Graph Foundation Model (GFM) that generalizes to previously unseen graphs and delivers a three to forty times boost in precision ...

ABSTRACT: The rapid advancements in large language models (LLMs) have led to an exponential increase in survey papers, making it challenging to systematically track and analyze their evolving taxonomy ...

1 College of Computer Science and Engineering, Changsha University, Changsha, Hunan, China 2 Department of Information and Computing Science, College of Mathematics, Changsha University, Changsha, ...

Abstract: Graph Convolutional Networks (GCNs) have been widely studied for semi-supervised learning tasks. It is known that the graph convolution operations in most of existing GCNs are composed of ...

Abstract: Graph-based semi-supervised learning has been shown to be one of the most effective classification approaches, as it can exploit connectivity patterns between labeled and unlabeled samples ...