A Simple Hypergraph Kernel Convolution based on Discounted Markov Diffusion Process

no code implementations • 30 Oct 2022 • Fuyang Li, Jiying Zhang, Xi Xiao, Bin Zhang, Dijun Luo

This paper proposes a two-phase paradigm to aggregate comprehensive information on discrete structures leading to a Discount Markov Diffusion Learnable Kernel (DMDLK).

Node Classification Transductive Learning

Hypergraph Convolutional Networks via Equivalency between Hypergraphs and Undirected Graphs

2 code implementations • 31 Mar 2022 • Jiying Zhang, Fuyang Li, Xi Xiao, Tingyang Xu, Yu Rong, Junzhou Huang, Yatao Bian

As a powerful tool for modeling complex relationships, hypergraphs are gaining popularity from the graph learning community.

Graph Learning

Improving Stack Overflow question title generation with copying enhanced CodeBERT model and bi-modal information

1 code implementation • 27 Sep 2021 • Fengji Zhang, Xiao Yu, Jacky Keung, Fuyang Li, Zhiwen Xie, Zhen Yang, Caoyuan Ma, Zhimin Zhang

However, only using the code snippets in the question body cannot provide sufficient information for title generation, and LSTMs cannot capture the long-range dependencies between tokens.