Contrastive Meta-Learning for Few-shot Node Classification-Reference-Cited by-同舟云学术

Contrastive Meta-Learning for Few-shot Node Classification

Published:2023-08-04 Issue: Volume: Page:
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Container-title:Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Wang Song¹^ORCID,Tan Zhen²^ORCID,Liu Huan³^ORCID,Li Jundong¹^ORCID

Affiliation:

1. University of Virginia, Charlottesville, VA, USA

2. Arizona State University, Tempe, AZ, USA

3. University of Virginia, Tempe, AZ, USA

Funder

Commonwealth Cyber Initiative awards

JP Morgan Chase Faculty Research Award

Cisco Faculty Research Award

Jefferson Lab subcontrac

IIS

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3580305.3599288

Reference60 articles.

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4. Ting Chen Simon Kornblith Mohammad Norouzi and Geoffrey Hinton. 2020. A simple framework for contrastive learning of visual representations. In ICML. PMLR 1597--1607. Ting Chen Simon Kornblith Mohammad Norouzi and Geoffrey Hinton. 2020. A simple framework for contrastive learning of visual representations. In ICML. PMLR 1597--1607.

5. Kaize Ding Jundong Li Nitin Agarwal and Huan Liu. 2020a. Inductive anomaly detection on attributed networks. In IJCAI. Kaize Ding Jundong Li Nitin Agarwal and Huan Liu. 2020a. Inductive anomaly detection on attributed networks. In IJCAI.

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