no code implementations • 5 Apr 2024 • Tengfei Ma, Xiang Song, Wen Tao, Mufei Li, Jiani Zhang, Xiaoqin Pan, Jianxin Lin, Bosheng Song, Xiangxiang Zeng
Knowledge graph completion (KGC) aims to alleviate the inherent incompleteness of knowledge graphs (KGs), which is a critical task for various applications, such as recommendations on the web.
1 code implementation • 20 Oct 2023 • Mufei Li, Eleonora Kreačić, Vamsi K. Potluru, Pan Li
However, these models face challenges in generating large attributed graphs due to the complex attribute-structure correlations and the large size of these graphs.
1 code implementation • 27 Nov 2021 • Fabio Broccatelli, Richard Trager, Michael Reutlinger, George Karypis, Mufei Li
In this work, we benchmark a variety of single- and multi-task graph neural network (GNN) models against lower-bar and higher-bar traditional machine learning approaches employing human engineered molecular features.
1 code implementation • 27 Jun 2021 • Mufei Li, Jinjing Zhou, Jiajing Hu, Wenxuan Fan, Yangkang Zhang, Yaxin Gu, George Karypis
Graph neural networks (GNNs) constitute a class of deep learning methods for graph data.
no code implementations • 25 Sep 2019 • Mufei Li, Hao Zhang, Xingjian Shi, Minjie Wang, Yixing Guan, Zheng Zhang
Does attention matter and, if so, when and how?
7 code implementations • 3 Sep 2019 • Minjie Wang, Da Zheng, Zihao Ye, Quan Gan, Mufei Li, Xiang Song, Jinjing Zhou, Chao Ma, Lingfan Yu, Yu Gai, Tianjun Xiao, Tong He, George Karypis, Jinyang Li, Zheng Zhang
Advancing research in the emerging field of deep graph learning requires new tools to support tensor computation over graphs.
Ranked #35 on Node Classification on Cora