1. Balažević, I., Allen, C., & Hospedales, T. (2019). TuckER: Tensor Factorization for Knowledge Graph Completion. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pp. 5185–5194.
2. Battaglia, P.W., Hamrick, J.B., Bapst, V., Sanchez-Gonzalez, A., Zambaldi, V., Malinowski, M., Tacchetti, A., Raposo, D., Santoro, A., Faulkner, R., Gulcehre, C., Song, F., Ballard, A., Gilmer, J., Dahl, G., Vaswani, A., Allen, K., Nash, C., Langston, V., Dyer, C., Heess, N., Wierstra, D., Kohli, P., Botvinick, M., Vinyals, O., Li, Y., Pascanu, R., 2018. Relational inductive biases, deep learning, and graph networks.
3. Translating Embeddings for Modeling Multi-relational Data;Bordes,2013
4. Chen, H., Yin, H., Sun, X., Chen, T., Gabrys, B., Musial, K., 2020. Multi-level Graph Convolutional Networks for Cross-platform Anchor Link Prediction.
5. Fatemi, B., Taslakian, P., Vazquez, D., Poole, D., 2021. Knowledge Hypergraphs: Prediction beyond Binary Relations, in: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI’20.