Publisher
Springer Nature Switzerland
Reference22 articles.
1. Bronstein, M.M., Bruna, J., LeCun, Y., Szlam, A., Vandergheynst, P.: Geometric deep learning: going beyond euclidean data. IEEE Signal Process. Mag. 34, 18–42 (2017). https://doi.org/10.1109/MSP.2017.2693418
2. Zhou, J., Cui, G., Hu, S., Zhang, Z., Yang, C., Liu, Z., Wang, L., Li, C., Sun, M.: Graph neural networks: a review of methods and applications. AI Open. 1, 57–81 (2020). https://doi.org/10.1016/j.aiopen.2021.01.001
3. Kipf, T.N., Welling, M.: Semi-supervised classification with graph convolutional networks. arXiv1609.02907 (2016)
4. Veličković, P., Cucurull, G., Casanova, A., Romero, A., Lio, P., Bengio, Y.: Graph attention networks. arXiv1710.10903 (2017)
5. Zhang, D., Yao, L., Chen, K., Wang, S., Haghighi, P.D., Sullivan, C.: A graph-based hierarchical attention model for movement intention detection from EEG signals. IEEE Trans. Neural Syst. Rehabil. Eng. 27, 2247–2253 (2019). https://doi.org/10.1109/TNSRE.2019.2943362