1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.CV2025★ 1 cited
Rethinking Multimodal Point Cloud Completion: A Completion-by-Correction Perspective
Wang Luo, Di Wu, Hengyuan Na +3
Point cloud completion aims to reconstruct complete 3D shapes from partial observations, which is a challenging problem due to severe occlusions and missing geometry. Despite recen…
cs.LG2025
Towards Effective Federated Graph Foundation Model via Mitigating Knowledge Entanglement
Yinlin Zhu, Xunkai Li, Jishuo Jia +3
Recent advances in graph machine learning have shifted to data-centric paradigms, driven by two emerging fields: (1) Federated graph learning (FGL) enables multi-client collaborati…
cs.LG2024
Federated Continual Graph Learning
Yinlin Zhu, Miao Hu, Di Wu
Managing evolving graph data presents substantial challenges in storage and privacy, and training graph neural networks (GNNs) on such data often leads to catastrophic forgetting,…