Robust Mid-Pass Filtering Graph Convolutional Networks-Reference-Cited by-同舟云学术

Robust Mid-Pass Filtering Graph Convolutional Networks

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

Huang Jincheng¹^ORCID,Du Lun²^ORCID,Chen Xu³^ORCID,Fu Qiang³^ORCID,Han Shi³^ORCID,Zhang Dongmei³^ORCID

Affiliation:

1. School of Computer Science, Southwest Petroleum University, China

2. Microsoft Research Aisa, China

3. Microsoft Research Asia, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3543507.3583335

Reference47 articles.

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2. Aleksandar Bojchevski and Stephan Günnemann . 2017. Deep gaussian embedding of graphs: Unsupervised inductive learning via ranking. arXiv preprint arXiv:1707.03815 ( 2017 ). Aleksandar Bojchevski and Stephan Günnemann. 2017. Deep gaussian embedding of graphs: Unsupervised inductive learning via ranking. arXiv preprint arXiv:1707.03815 (2017).

3. Joan Bruna , Wojciech Zaremba , Arthur Szlam , and Yann LeCun . 2013. Spectral networks and locally connected networks on graphs. arXiv preprint arXiv:1312.6203 ( 2013 ). Joan Bruna, Wojciech Zaremba, Arthur Szlam, and Yann LeCun. 2013. Spectral networks and locally connected networks on graphs. arXiv preprint arXiv:1312.6203 (2013).

4. Not all low-pass filters are robust in graph convolutional networks;Chang Heng;Advances in Neural Information Processing Systems,2021

5. Zhixian Chen , Tengfei Ma , and Yang Wang . 2022. When Does A Spectral Graph Neural Network Fail in Node Classification?arXiv preprint arXiv:2202.07902 ( 2022 ). Zhixian Chen, Tengfei Ma, and Yang Wang. 2022. When Does A Spectral Graph Neural Network Fail in Node Classification?arXiv preprint arXiv:2202.07902 (2022).

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