Graph Cross Supervised Learning via Generalized Knowledge

Author:

Yuan Xiangchi1ORCID,Tian Yijun2ORCID,Zhang Chunhui3ORCID,Ye Yanfang2ORCID,Chawla Nitesh V.2ORCID,Zhang Chuxu4ORCID

Affiliation:

1. Brandeis University & Georgia Institute of Technology, Waltham, MA, USA

2. University of Notre Dame, South Bend, IN, USA

3. Dartmouth College, Hanover, NH, USA

4. Brandeis University, Waltham, MA, USA

Funder

NSF (National Science Foundation)

Publisher

ACM

Reference58 articles.

1. Peter W Battaglia, Jessica B Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinicius Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, et al. Relational inductive biases, deep learning, and graph networks. arXiv preprint arXiv:1806.01261, 2018.

2. Junjie Chen, Li Niu, Liu Liu, and Liqing Zhang. Weak-shot fine-grained classification via similarity transfer. In NeurIPS, 2021.

3. Ming Cheng, Ziyi Zhou, Bowen Zhang, Ziyu Wang, Jiaqi Gan, Ziang Ren, Weiqi Feng, Yi Lyu, Hefan Zhang, and Xingjian Diao. Efflex: Efficient and flexible pipeline for spatio-temporal trajectory graph modeling and representation learning. arXiv preprint arXiv:2404.12400, 2024.

4. NRGNN

5. Wenqi Fan, Yao Ma, Qing Li, Yuan He, Eric Zhao, Jiliang Tang, and Dawei Yin. Graph neural networks for social recommendation. In WWW, 2019.

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