1. Ripple walk training: A subgraphbased training framework for large and deep graph neural network;J Bai;International Joint Conference on Neural Networks (IJCNN),2021
2. Fastgcn: Fast learning with graph convolutional networks via importance sampling;J Chen;International Conference on Learning Representations (ICLR),2018
3. Cluster-gcn: An efficient algorithm for training deep and large graph convolutional networks;W L Chiang;Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining,2019
4. Mrgat: multi-relational graph attention network for knowledge graph completion;G Dai;Neural Networks,2022
5. 2023a. Dual-hand motion capture by using biological inspiration for bionic bimanual robot teleoperation;Q Gao;Cyborg and Bionic Systems