Author:
Hao Yunzhi,Wang Yu,Liu Shunyu,Zheng Tongya,Wang Xingen,Wang Xinyu,Song Mingli,Huang Wenqi,Chen Chun
Publisher
Springer Nature Singapore
Reference35 articles.
1. Ancona, M., Ceolini, E., Öztireli, C., Gross, M.: Towards better understanding of gradient-based attribution methods for deep neural networks. arXiv preprint arXiv:1711.06104 (2017)
2. de Carvalho, M.V., Pratama, M., Zhang, J., San, Y.: Class-incremental learning via knowledge amalgamation. In: ECML/PKDD (2022)
3. Chen, J., Ma, T., Xiao, C.: Fastgcn: fast learning with graph convolutional networks via importance sampling. arXiv preprint arXiv:1801.10247 (2018)
4. Chiang, W.L., Liu, X., Si, S., Li, Y., Bengio, S., Hsieh, C.J.: Cluster-gcn: an efficient algorithm for training deep and large graph convolutional networks. In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, pp. 257–266 (2019)
5. Deng, X., Zhang, Z.: Graph-free knowledge distillation for graph neural networks. In: The 30th International Joint Conference on Artificial Intelligence (2021)