4 papers
Node-level Graph Neural Architecture Search Framework
Lintao Yanga, Sirui Lia, Yaqing Wang +4
In recent years, Graph Neural Networks (GNNs) and architecture search frameworks have gained extensive application in non-Euclidean data processing, attributable to their superior…
AutoHGNN: Robust and Efficient Neural Architecture Search for Hypergraph Neural Networks
Sirui Li, Pietro Liò b, Xinsheng Li +2
Hypergraph neural networks have achieved significant success in recent years. However, manual architecture crafting is labor-intensive and often fails to capture complex, higher-or…
A Multi-View Consistency Framework with Semi-Supervised Domain Adaptation
Yuting Hong, Li Dong, Xiaojie Qiu +4
Semi-Supervised Domain Adaptation (SSDA) leverages knowledge from a fully labeled source domain to classify data in a partially labeled target domain. Due to the limited number of…
Directed Link Prediction using GNN with Local and Global Feature Fusion
Yuyang Zhang, Xu Shen, Yu Xie +3
Link prediction is a classical problem in graph analysis with many practical applications. For directed graphs, recently developed deep learning approaches typically analyze node s…