HONGJIA XU — accepted AI-conference papers

2025

Understanding and Enhancing Message Passing on Heterophilic Graphs via Compatibility Matrix

Zhuonan Zheng, Yuanchen Bei, Zhiyao Zhou, Sheng Zhou, Yao Ma, Ming Gu +3

NeurIPS 2025poster

Graph Neural Networks (GNNs) excel in graph mining tasks thanks to their message-passing mechanism, which aligns with the homophily assumption. However, connected nodes can also exhibit inconsistent behaviors, termed heterophilic patterns, sparking interest in heterophilic GNNs (HTGNNs). Although th…

Cited by 0 Source ↗Scholar ↗

2022

Hilbert Distillation for Cross-Dimensionality Networks

Dian Qin, Haishuai Wang, Zhe Liu, HONGJIA XU, Sheng Zhou, Jiajun Bu

NeurIPS 2022accept

3D convolutional neural networks have revealed superior performance in processing volumetric data such as video and medical imaging. However, the competitive performance by leveraging 3D networks results in huge computational costs, which are far beyond that of 2D networks. In this paper, we propose…

Cited by 7 Source ↗PDF ↗code ↗Scholar ↗