6 citations · 6 across the 4 of their papers we have counts for
4 papers
A Causal Disentangled Multi-Granularity Graph Classification Method
Yuan Li, Li Liu, Penggang Chen +2
Graph data widely exists in real life, with large amounts of data and complex structures. It is necessary to map graph data to low-dimensional embedding. Graph classification, a cr…
MSFormer: A Skeleton-multiview Fusion Method For Tooth Instance Segmentation
Yuan Li, Huan Liu, Yubo Tao +4
Recently, deep learning-based tooth segmentation methods have been limited by the expensive and time-consuming processes of data collection and labeling. Achieving high-precision s…
Trace Monomial Boolean Functions with Large High-Order Nonlinearities
Jinjie Gao, Haibin Kan, Yuan Li +2
Exhibiting an explicit Boolean function with a large high-order nonlinearity is an important problem in cryptography, coding theory, and computational complexity. We prove lower bo…
A Survey of Imbalanced Learning on Graphs: Problems, Techniques, and Future Directions
Zemin Liu, Yuan Li, Nan Chen +3
Graphs represent interconnected structures prevalent in a myriad of real-world scenarios. Effective graph analytics, such as graph learning methods, enables users to gain profound…