3 papers
cs.LG2025
CLEAR: Cluster-based Prompt Learning on Heterogeneous Graphs
Feiyang Wang, Zhongbao Zhang, Junda Ye +2
Prompt learning has attracted increasing attention in the graph domain as a means to bridge the gap between pretext and downstream tasks. Existing studies on heterogeneous graph pr…
cs.LG2024
Contrastive Sequential Interaction Network Learning on Co-Evolving Riemannian Spaces
Li Sun, Junda Ye, Jiawei Zhang +4
The sequential interaction network usually find itself in a variety of applications, e.g., recommender system. Herein, inferring future interaction is of fundamental importance, an…
cs.LG2024
Motif-aware Riemannian Graph Neural Network with Generative-Contrastive Learning
Li Sun, Zhenhao Huang, Zixi Wang +3
Graphs are typical non-Euclidean data of complex structures. In recent years, Riemannian graph representation learning has emerged as an exciting alternative to Euclidean ones. How…