An Energy-centric Framework for Category-free Out-of-distribution Node Detection in Graphs

Author:

Gong Zheng1ORCID,Sun Ying1ORCID

Affiliation:

1. Thrust of Artificial Intelligence, Hong Kong University of Science and Technology (Guangzhou), Guangzhou, Guangdong, China

Funder

the Education Bureau of Guangzhou Municipality

the Natural Science Foundation of Guangdong Province

the National Natural Science Foundation of China

the Guangzhou-HKUST(GZ) Joint Funding Program

the National Key Research and Development Program of China

the Fundamental Research Project of Guangzhou

Publisher

ACM

Reference61 articles.

1. Liron Bergman and Yedid Hoshen. 2020. Classification-Based Anomaly Detection for General Data. In Proc. of ICLR.

2. LOF

3. Measuring and Relieving the Over-Smoothing Problem for Graph Neural Networks from the Topological View

4. Liyi Chen, Zhi Li, Yijun Wang, Tong Xu, Zhefeng Wang, and Enhong Chen. 2020. MMEA: entity alignment for multi-modal knowledge graph. In Knowledge Science, Engineering and Management: 13th International Conference, KSEM 2020, Hangzhou, China, August 28--30, 2020, Proceedings, Part I 13.

5. Generative Adversarial Attributed Network Anomaly Detection

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