Publications (27)
Deep Hypergraph Structure Learning
Zizhao Zhang, Yifan Feng, Shihui Ying +1
Learning on high-order correlation has shown superiority in data representation learning, where hypergraph has been widely used in recent decades. The performance of hypergraph-bas…
Open set label noise learning with robust sample selection and margin-guided module
Yuandi Zhao, Qianxi Xia, Yang Sun +3
In recent years, the remarkable success of deep neural networks (DNNs) in computer vision is largely due to large-scale, high-quality labeled datasets. Training directly on real-wo…
LightHGNN: Distilling Hypergraph Neural Networks into MLPs for Faster Inference
Yifan Feng, Yihe Luo, Shihui Ying +1
Hypergraph Neural Networks (HGNNs) have recently attracted much attention and exhibited satisfactory performance due to their superiority in high-order correlation modeling. Howeve…
Pseudo-Data based Self-Supervised Federated Learning for Classification of Histopathological Images
Jun Shi, Yuanming Zhang, Zheng Li +4
Computer-aided diagnosis (CAD) can help pathologists improve diagnostic accuracy together with consistency and repeatability for cancers. However, the CAD models trained with the h…
Fast MRI Reconstruction via Edge Attention
Hanhui Yang, Juncheng Li, Lok Ming Lui +3
Fast and accurate MRI reconstruction is a key concern in modern clinical practice. Recently, numerous Deep-Learning methods have been proposed for MRI reconstruction, however, they…
Hypergraph as Language
Mengqi Lei, Guohuan Xie, Shihui Ying +4
Large language models (LLMs) have recently shown strong potential in modeling relational structures. However, existing approaches remain fundamentally graph-centric: they focus on…