9 citations · 12 across the 10 of their papers we have counts for
10 papers
Hyper-Fold: Exploring the Expressive Limit of Sequence-Geometry Learning for Proteins via Hypergraph Modeling
Yifan Feng, Guanjie Cheng, Shihui Ying +2
Protein structure modeling rests on a single computational primitive: the interaction between what a residue is (sequence content) and where it sits (three-dimensional geometry). W…
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…
HNS: An Efficient Hermite Neural Solver for Solving Time-Fractional Partial Differential Equations
Jie Hou, Zhiying Ma, Shihui Ying +1
Neural network solvers represent an innovative and promising approach for tackling time-fractional partial differential equations by utilizing deep learning techniques. L1 interpol…
Hypergraph Isomorphism Computation
Yifan Feng, Jiashu Han, Shihui Ying +1
The isomorphism problem is a fundamental problem in network analysis, which involves capturing both low-order and high-order structural information. In terms of extracting low-orde…
Weakly Supervised Lesion Detection and Diagnosis for Breast Cancers with Partially Annotated Ultrasound Images
Jian Wang, Liang Qiao, Shichong Zhou +6
Deep learning (DL) has proven highly effective for ultrasound-based computer-aided diagnosis (CAD) of breast cancers. In an automaticCAD system, lesion detection is critical for th…
Multi-scale Efficient Graph-Transformer for Whole Slide Image Classification
Saisai Ding, Juncheng Li, Jun Wang +2
The multi-scale information among the whole slide images (WSIs) is essential for cancer diagnosis. Although the existing multi-scale vision Transformer has shown its effectiveness…