5 citations · 6 across the 10 of their papers we have counts for
4 papers · 1 filter
Multi-Modal Molecular Representation Learning via Structure Awareness
Rong Yin, Ruyue Liu, Xiaoshuai Hao +4
Accurate extraction of molecular representations is a critical step in the drug discovery process. In recent years, significant progress has been made in molecular representation l…
AS-GCL: Asymmetric Spectral Augmentation on Graph Contrastive Learning
Ruyue Liu, Rong Yin, Yong Liu +4
Graph Contrastive Learning (GCL) has emerged as the foremost approach for self-supervised learning on graph-structured data. GCL reduces reliance on labeled data by learning robust…
Communication-Efficient Personalized Federal Graph Learning via Low-Rank Decomposition
Ruyue Liu, Rong Yin, Xiangzhen Bo +5
Federated graph learning (FGL) has gained significant attention for enabling heterogeneous clients to process their private graph data locally while interacting with a centralized…
FTF-ER: Feature-Topology Fusion-Based Experience Replay Method for Continual Graph Learning
Jinhui Pang, Changqing Lin, Xiaoshuai Hao +5
Continual graph learning (CGL) is an important and challenging task that aims to extend static GNNs to dynamic task flow scenarios. As one of the mainstream CGL methods, the experi…