Ming Li

Full Professor@Zhejiang Normal University·中国·OpenReview

研究方向

hypergraph learning · graph machine learning · hypergraph neural networks · educational data mining · graph data mining · graph learning · graph neural networks · graph representation learning · geometric deep learning · statistical machine learning · neural networks with random weights · randomized learning techniques for neural networks · random features · learning theory

3.0

From Contextual Distributions to Messages: Entropy-Guided GNNs

ICLR 2026Rejected

7.8

MultiNet: Adaptive Multi-Viewed Subgraph Convolutional Networks for Graph Classification

NeurIPS 2025Poster

7.2

EduLLM: Leveraging Large Language Models and Framelet-Based Signed Hypergraph Neural Networks for Student Performance Prediction

ICML 2025Poster

一作

6.6

ENAHPool: The Edge-Node Attention-based Hierarchical Pooling for Graph Neural Networks

合作者 (20)

Ming Li

From Contextual Distributions to Messages: Entropy-Guided GNNs

MultiNet: Adaptive Multi-Viewed Subgraph Convolutional Networks for Graph Classification

EduLLM: Leveraging Large Language Models and Framelet-Based Signed Hypergraph Neural Networks for Student Performance Prediction

Test-Time Graph Neural Dataset Search With Generative Projection

HyperMixup: Hypergraph-Augmented with Higher-order Information Mixup

HyperNear: Unnoticeable Node Injection Attacks on Hypergraph Neural Networks

ENAHPool: The Edge-Node Attention-based Hierarchical Pooling for Graph Neural Networks