GTAGCN: Generalized Topology Adaptive Graph Convolutional Networks

arXiv:2403.15077v1 Announce Type: new
Abstract: Graph Neural Networks (GNN) have emerged as a popular and standard approach for learning from graph-structured data. The literature on GNN highlights the potential of this evolving research area and its widespread adoption in real-life applications. However, most of the approaches are either new in concept or derived from specific techniques. Therefore, the potential of more than one approach in hybrid form has not been studied extensively, which can be well utilized for sequenced data …

abstract adoption applications arxiv concept cs.lg data generalized gnn graph graph neural networks highlights however life literature networks neural networks popular research standard structured data topology type