HINormer: Representation Learning On Heterogeneous Information Networks with Graph Transformer-Reference-Cited by-同舟云学术

HINormer: Representation Learning On Heterogeneous Information Networks with Graph Transformer

Published:2023-04-30 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the ACM Web Conference 2023
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Author:

Mao Qiheng¹^ORCID,Liu Zemin²^ORCID,Liu Chenghao³^ORCID,Sun Jianling¹^ORCID

Affiliation:

1. Zhejiang University, China and Alibaba-Zhejiang University Joint Institute of Frontier Technologies, China

2. National University of Singapore, Singapore

3. Salesforce Research Asia, Singapore

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3543507.3583493

Reference62 articles.

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

3. Freebase

4. Shaked Brody , Uri Alon , and Eran Yahav . 2021. How attentive are graph attention networks?arXiv preprint arXiv:2105.14491 ( 2021 ). Shaked Brody, Uri Alon, and Eran Yahav. 2021. How attentive are graph attention networks?arXiv preprint arXiv:2105.14491 (2021).

5. A comprehensive survey of graph embedding: Problems, techniques, and applications;Cai Hongyun;IEEE TKDE,2018

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