Cuiying Huo

Multi-Semantic Aware Self-Supervised Learning for Multi-Label Node Classification

Graph self-supervised learning aims to mine intrinsic signals from graph data itself to train models. It enables the acquisition of high-quality representations without manual annotations, making it suitable for various label-scarce scenarios and thus garnering substantial interest. Existing graph self-supervised metho...