3 code implementations • 10 May 2023 • Mingqi Yang, Wenjie Feng, Yanming Shen, Bryan Hooi
Proposing an effective and flexible matrix to represent a graph is a fundamental challenge that has been explored from multiple perspectives, e. g., filtering in Graph Fourier Transforms.
Ranked #5 on Graph Regression on ZINC
1 code implementation • 11 Jun 2022 • Mingqi Yang, Yanming Shen, Heng Qi, BaoCai Yin
Task-relevant structures can be $localized$ or $sparse$ which are only involved in subgraphs or characterized by the interactions of subgraphs (a hierarchical perspective).
1 code implementation • 14 Dec 2021 • Mingqi Yang, Yanming Shen, Rui Li, Heng Qi, Qiang Zhang, BaoCai Yin
Many improvements on GNNs can be deemed as operations on the spectrum of the underlying graph matrix, which motivates us to directly study the characteristics of the spectrum and their effects on GNN performance.
Ranked #3 on Graph Classification on ENZYMES
4 code implementations • 15 Jun 2021 • Chengxuan Ying, Mingqi Yang, Shuxin Zheng, Guolin Ke, Shengjie Luo, Tianle Cai, Chenglin Wu, Yuxin Wang, Yanming Shen, Di He
In this technical report, we present our solution of KDD Cup 2021 OGB Large-Scale Challenge - PCQM4M-LSC Track.
1 code implementation • 14 Dec 2020 • Mingqi Yang, Yanming Shen, Heng Qi, BaoCai Yin
Recently, the Weisfeiler-Lehman (WL) graph isomorphism test was used to measure the expressiveness of graph neural networks (GNNs), showing that the neighborhood aggregation GNNs were at most as powerful as 1-WL test in distinguishing graph structures.
Ranked #1 on Graph Property Prediction on ogbg-ppa