Qi Zhu, Natalia Ponomareva, Jiawei Han 0001, Bryan Perozzi. Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training data. In Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan, editors, Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual. pages 27965-27977, 2021. [doi]
@inproceedings{ZhuPHP21,
title = {Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training data},
author = {Qi Zhu and Natalia Ponomareva and Jiawei Han 0001 and Bryan Perozzi},
year = {2021},
url = {https://proceedings.neurips.cc/paper/2021/hash/eb55e369affa90f77dd7dc9e2cd33b16-Abstract.html},
researchr = {https://researchr.org/publication/ZhuPHP21},
cites = {0},
citedby = {0},
pages = {27965-27977},
booktitle = {Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual},
editor = {Marc'Aurelio Ranzato and Alina Beygelzimer and Yann N. Dauphin and Percy Liang and Jennifer Wortman Vaughan},
}