A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide

Author:

Kim Sunwoo1ORCID,Lee Soo Yong1ORCID,Gao Yue2ORCID,Antelmi Alessia3ORCID,Polato Mirko3ORCID,Shin Kijung1ORCID

Affiliation:

1. KAIST, Seoul, Republic of Korea

2. Tsinghua University, Beijing, China

3. University of Turin, Turin, Italy

Funder

Institute of Information & Communications Technology Planning & Evaluation

European Union ? NextGenerationEU

Publisher

ACM

Reference177 articles.

1. Shivam Agarwal, Ramit Sawhney, Megh Thakkar, Preslav Nakov, Jiawei Han, and Tyler Derr. 2022. Think: Temporal hypergraph hyperbolic network. In ICDM.

2. Ryan Aponte, Ryan A Rossi, Shunan Guo, Jane Hoffswell, Nedim Lipka, Chang Xiao, Gromit Chan, Eunyee Koh, and Nesreen Ahmed. 2022. A hypergraph neural network framework for learning hyperedge-dependent node embeddings. arXiv preprint arXiv:2212.14077 (2022).

3. Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton. 2016. Layer normalization. arXiv preprint arXiv:1607.06450 (2016).

4. Multi-Scale Representation Learning on Hypergraph for 3D Shape Retrieval and Recognition

5. Hypergraph convolution and hypergraph attention

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