3 papers
cs.LG2026
T-GINEE: A Tensor-Based Multilayer Graph Representation Learning
Maolin Wang, Ziting Mai, Xuhui Chen +9
Traditional network analysis focuses on single-layer networks, real-world systems often form multilayer networks with multiple relationship types. However, existing methods typical…
cs.LG2025
Disentangled Graph Representation Based on Substructure-Aware Graph Optimal Matching Kernel Convolutional Networks
Mao Wang, Tao Wu, Xingping Xian +3
Graphs effectively characterize relational data, driving graph representation learning methods that uncover underlying predictive information. As state-of-the-art approaches, Graph…
cs.LG2025
Tensor Networks Meet Neural Networks: A Survey and Future Perspectives
Maolin Wang, Yu Pan, Zenglin Xu +4
Tensor networks (TNs) and neural networks (NNs) are two fundamental data modeling approaches. TNs were introduced to solve the curse of dimensionality in large-scale tensors by con…