1 citations · 1 across the 10 of their papers we have counts for
10 papers
Hyperbolic Continuous Structural Entropy for Hierarchical Clustering
Guangjie Zeng, Hao Peng, Angsheng Li +5
Hierarchical clustering is a fundamental machine-learning technique for grouping data points into dendrograms. However, existing hierarchical clustering methods encounter two prima…
STAMImputer: Spatio-Temporal Attention MoE for Traffic Data Imputation
Yiming Wang, Hao Peng, Senzhang Wang +4
Traffic data imputation is fundamentally important to support various applications in intelligent transportation systems such as traffic flow prediction. However, existing time-to-…
Unsupervised Graph Clustering with Deep Structural Entropy
Jingyun Zhang, Hao Peng, Li Sun +3
Research on Graph Structure Learning (GSL) provides key insights for graph-based clustering, yet current methods like Graph Neural Networks (GNNs), Graph Attention Networks (GATs),…
ASIL: Augmented Structural Information Learning for Deep Graph Clustering in Hyperbolic Space
Li Sun, Zhenhao Huang, Yujie Wang +4
Graph clustering is a longstanding topic in machine learning. Recently, deep methods have achieved results but still require predefined cluster numbers K and struggle with imbalanc…
Pioneer: Physics-informed Riemannian Graph ODE for Entropy-increasing Dynamics
Li Sun, Ziheng Zhang, Zixi Wang +5
Dynamic interacting system modeling is important for understanding and simulating real world systems. The system is typically described as a graph, where multiple objects dynamical…
RiemannGFM: Learning a Graph Foundation Model from Riemannian Geometry
Li Sun, Zhenhao Huang, Suyang Zhou +3
The foundation model has heralded a new era in artificial intelligence, pretraining a single model to offer cross-domain transferability on different datasets. Graph neural network…
Structural Entropy Guided Probabilistic Coding
Xiang Huang, Hao Peng, Li Sun +4
Probabilistic embeddings have several advantages over deterministic embeddings as they map each data point to a distribution, which better describes the uncertainty and complexity…
R-ODE: Ricci Curvature Tells When You Will be Informed
Li Sun, Jingbin Hu, Mengjie Li +1
Information diffusion prediction is fundamental to understand the structure and organization of the online social networks, and plays a crucial role to blocking rumor spread, influ…
LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering
Li Sun, Zhenhao Huang, Hao Peng +3
Graph clustering is a fundamental problem in machine learning. Deep learning methods achieve the state-of-the-art results in recent years, but they still cannot work without predef…
MultiSPANS: A Multi-range Spatial-Temporal Transformer Network for Traffic Forecast via Structural Entropy Optimization
Dongcheng Zou, Senzhang Wang, Xuefeng Li +5
Traffic forecasting is a complex multivariate time-series regression task of paramount importance for traffic management and planning. However, existing approaches often struggle t…