Datasets, tasks, and training methods for large-scale hypergraph learning-Reference-Cited by-同舟云学术

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Datasets, tasks, and training methods for large-scale hypergraph learning

Published:2023-07-26 Issue:6 Volume:37 Page:2216-2254
ISSN:1384-5810
Container-title:Data Mining and Knowledge Discovery
language:en
Short-container-title:Data Min Knowl Disc

Author:

Kim Sunwoo,Lee Dongjin,Kim Yul,Park Jungho,Hwang Taeho,Shin Kijung^ORCID

Funder

National Research Foundation of Korea

Samsung Electronics Co., Ltd.

Institute for Information and Communications Technology Promotion

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Computer Science Applications,Information Systems

Link

https://link.springer.com/content/pdf/10.1007/s10618-023-00952-6.pdf

Reference100 articles.

1. Addanki R, Battaglia P, Budden D, et al (2021) Large-scale graph representation learning with very deep GNNs and self-supervision. arXiv:2107.09422, https://doi.org/10.48550/arXiv.2107.09422

2. Ahmed I, Galoppo T, Hu X et al (2021) Graph regularized autoencoder and its application in unsupervised anomaly detection. IEEE Trans Pattern Anal Mach Intell (TPAMI) 44(8):4110–4124. https://doi.org/10.1109/TPAMI.2021.3066111

3. Arya D, Gupta DK, Rudinac S, et al (2020) HyperSAGE: Generalizing inductive representation learning on hypergraphs. arXiv:2010.04558, https://doi.org/10.48550/arXiv.2010.04558

4. Bai S, Zhang F, Torr PH (2021) Hypergraph convolution and hypergraph attention. Pattern Recogn 110(107):637. https://doi.org/10.1016/j.patcog.2020.107637

5. Benson AR, Abebe R, Schaub MT et al (2018) Simplicial closure and higher-order link prediction. Proceed Nat Acad Sci 115(48):E11221–E11230. https://doi.org/10.1073/pnas.1800683115

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1. A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

2. Higher-Order Networks Representation and Learning: A Survey;ACM SIGKDD Explorations Newsletter;2024-07-24

3. HypergraphRepository: A Community-Driven and Interactive Hypernetwork Data Collection;Lecture Notes in Computer Science;2024

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