Graph Condensation for Open-World Graph Learning

Author:

Gao Xinyi1ORCID,Chen Tong1ORCID,Zhang Wentao2ORCID,Li Yayong3ORCID,Sun Xiangguo4ORCID,Yin Hongzhi1ORCID

Affiliation:

1. The University of Queensland, Brisbane, Australia

2. Peking University, Beijing, China

3. Data 61, CSIRO, Brisbane, Australia

4. The Chinese University of Hong Kong, Hong Kong, China

Funder

Australian Research Council

Publisher

ACM

Reference52 articles.

1. Martin Arjovsky, Léon Bottou, Ishaan Gulrajani, and David Lopez-Paz. 2019. Invariant risk minimization. arXiv preprint arXiv:1907.02893 (2019).

2. Towards Open Set Deep Networks

3. Mucong Ding, Xiaoyu Liu, Tahseen Rabbani, Teresa Ranadive, Tai-Ching Tuan, and Furong Huang. 2022. Faster Hyperparameter Search for GNNs via Calibrated Dataset Condensation. arXiv (2022).

4. Kaituo Feng, Changsheng Li, Xiaolu Zhang, and Jun Zhou. 2023. Towards open temporal graph neural networks. International Conference on Learning Representations (2023).

5. Xinyi Gao, Tong Chen, Yilong Zang, Wentao Zhang, Quoc Viet Hung Nguyen, Kai Zheng, and Hongzhi Yin. 2024a. Graph Condensation for Inductive Node Representation Learning. In ICDE.

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