Shaonan Ma — accepted AI-conference papers

2025

HyperKAN: Hypergraph Representation Learning with Kolmogorov-Arnold Networks

Xiangfei Fang, Boying Wang, Chengying Huan, Shaonan Ma, Heng Zhang, Chen Zhao

ICASSP 2025accepted

Hypergraph representation learning has garnered increasing attention across various domains due to its capability to model high-order relationships. Traditional methods often rely on hypergraph neural networks (HNNs) employing messagepassing mechanisms to aggregate vertex and hyperedge features. How…

Cited by 0 Source ↗Scholar ↗

2025

HyperSF: A Hypergraph Representation Learning Method Based on Structural Fusion

Xiangfei Fang, Chengying Huan, Boying Wang, Shaonan Ma, Heng Zhang, Chen Zhao

ICASSP 2025accepted

Hypergraph Neural Networks (HNNs) have recently gained attention as a powerful approach for capturing high-order correlations through hypergraph-structured encoding and learning techniques. However, despite their potential, existing HNN methods often encounter over-smoothing issues, which limit thei…

Cited by 0 Source ↗Scholar ↗