1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2026
Synchronous Multi-view Neural Diffusion
Yongquan Shi, Weijun Huang, Yueyang Pi +3
Multi-view learning seeks to learn more comprehensive representations by exploiting the complementarity and consistency across diverse modalities or views. However, existing multi-…
cs.LG2025★ 1 cited
Simplifying Graph Convolutional Networks with Redundancy-Free Neighbors
Jielong Lu, Zhihao Wu, Zhiling Cai +2
In recent years, Graph Convolutional Networks (GCNs) have gained popularity for their exceptional ability to process graph-structured data. Existing GCN-based approaches typically…
cs.LG2024
SpreadFGL: Edge-Client Collaborative Federated Graph Learning with Adaptive Neighbor Generation
Luying Zhong, Yueyang Pi, Zheyi Chen +4
Federated Graph Learning (FGL) has garnered widespread attention by enabling collaborative training on multiple clients for semi-supervised classification tasks. However, most exis…